This book presents examples that illustrate the theory of mathematical statistics and details how to apply the methods for solving problems. While other books on the topic contain problems and exercises, they do not focus on problem solving. This book fills an important niche in the statistical theory literature by providing a theory/example/problem approach. Each chapter is divided into four parts: Part I provides the needed theory so readers can become familiar with the concepts, notations, and proven results; Part II presents examples from a variety of fields including engineering, mathematics, and statistics; Part III contains the problems for solutions; and Part IV features selected problems with solutions. Within the book's nine chapters, the authors provides 200 examples and over 300 problems, and solutions are provided for approximately 10% of the problems. Chapter coverage includes: Basic Probability Theory; Statistical Distributions; Sufficient Statistics and Information in Samples; Testing Statistical Hypothesis; Statistical Estimation; Confidence and Tolerance Intervals; Large Sample Theory for Estimation and Testing; Bayesian Analysis in Testing and Estimation; and Advanced Topics in Estimation Theory.
Keywords: Probability & Mathematical Statistics