Probability, Statistics, and Stochastic Processes

This text begins with chapters that develop probability theory and introduce the axioms of probability, random variables, and joint distributions. The next sections introduce limit theorems and simulation. Also included is a chapter on statistical inference, with a section on Bayesian statistics which is an important, though often neglected, topic for undergraduate-level texts. Markov chains in discrete and continuous time is also discussed within the book. More than 400 examples are interspersed throughout the text to help illustrate concepts and theory and to assist the reader to develop an intuitive sense of the subject. Readers will find many of the examples to be both entertaining and thought provoking. This is also true for the carefully selected problems that appear at the end of each chapter.