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 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.
General
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