Mathematical Statistics: Exercises and Solutions

Jun Shao is Professor of Statistics at the University of Wisconsin, Madison.

From the reviews: "This book contains 400 exercises with their detailed solutions. ... It has an extensive list of notations and terminologies and can be used as a stand-alone book. This book will be very useful to Statistics students studying towards an M.Sc or a Ph.D. degree, by helping them to develop problem solving skills ... . It will be useful to their teachers as a source of solved exercises. The list of 26 distributions given at the beginning will also be useful for ready reference." (Mausumi Bose, Sankhya, Vol. 67 (4), 2005) "The exercise book accompanies an excellent text book for a graduate course in mathematical statistics ... and is an excellent support for the book. The exercise book is excellent by itself also: a challenging collection of problems in mathematical statistics. ... Using both however, the textbook and the exercise book, the mathematical statistician will enjoy the wealth of interesting problems." (Gotz Uebe, Allgemeines Statistisches Archiv, Issue 2, 2005) "This book consists of solutions to 400 exercises in the general theory of mathematical statistics ... . The solutions of the exercises are thorough and explain the different steps in great detail. These solutions will certainly help students to a better understanding of the many complicated issues in the theory. This book is thus a valuable contribution to the teaching materials currently available." (Jon Stene, Mathematical Reviews, Issue 2006 b) "This collection consists of 400 exercises and their solutions. Most of the exercises (over 95%) are introduced in the cited textbook. ... The collection is a stand-alone book. It is written very rigorously and solutions are presented in detail. It can be recommended as a source of solved problems for teachers and students of advanced mathematical statistics." (EMS Newsletter, June, 2006)

• Probability Theory.- Fundamentals of Statistics.- Unbiased Estimation.- Estimation in Parametric Models.- Estimation in Nonparametric Models.- Hypothesis Tests.- Confidence Sets.