حل المسائل آمار ریاضیاتی شائو

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حل المسائل آمار ریاضیاتی

جون شائو

عنوان کتاب: حل المسائل آمار ریاضیاتی

نویسندگان: جون شائو

تعداد صفخات: ۳۸۴

فرمت: pdf

زبان: انگلیسی

ویرایش: —

درباره کتاب:

PREFACE

Since the publication of my book Mathematical Statistics (Shao, 2003), I have been asked many times for a solution manual to the exercises in my book. Without doubt, exercises form an important part of a textbook on mathematical statistics, not only in training students for their research ability in mathematical statistics but also in presenting many additional results as complementary material to the main text. Written solutions to these exercises are important for students who initially do not have the skills in solving these exercises completely and are very helpful for instructors of a mathematical statistics course (whether or not my book Mathematical Statistics is used as the textbook) in providing answers to students as well as finding additional examples to the main text. Motivated by this and encouraged by some of my colleagues and Springer-Verlag editor John Kimmel, I have completed this book, Mathematical Statistics: Exercises and Solutions.

This book consists of solutions to 400 exercises, over 95% of which are in my book Mathematical Statistics. Many of them are standard exercises that also appear in other textbooks listed in the references. It is only a partial solution manual to Mathematical Statistics (which contains over 900 exercises). However, the types of exercise in Mathematical Statistics not
selected in the current book are (1) exercises that are routine (each exercise selected in this book has a certain degree of difficulty), (2) exercises similar to one or several exercises selected in the current book, and (3) exercises for advanced materials that are often not included in a mathematical statistics course for first-year P.h.D. students in statistics (e.g., Edge worth expansions and second-order accuracy of confidence sets, empirical likelihoods, statistical functionals, generalized linear models, non-parametric tests, and theory for the bootstrap and jackknife, etc.). On the other hand, this is a stand-alone book, since exercises and solutions are comprehensible independently of their source for likely readers. To help readers not using this book together with Mathematical Statistics, lists of notation, terminology, and some probability distributions are given in the front of the book.

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