This new edition continues to illustrate the application of statistical methods to research across various disciplines, including medicine, engineering, business/finance, and the social sciences. Thoroughly revised and updated, the authors have refreshed this book to reflect the changes and current trends in statistical distibution theory that have occured since the publication of the previous edition eight years ago. The introductory chapters introduce the fundamental concepts of the distributions and the relationships between variables. For each distribution that follows, the key formulae, tables and diagrams are presented in a concise, user-friendly format. Key facts and formulas for forty major probability distributions are presented, making the book an ideal introduction to the general theory of statistical distributions as well as a quick reference on its basic principles. Newly added coverage includes the exploration of connections between distributions using conditioning; discussion of distributions not addressed in the previous edition (such as Generalized Student-t, binomial distribution, and triangular distribution); and a thorough review of conditional probability, conditional expectations, and joint and marginal distributions. A new chapter on statistical inference has also been added, illustrating modeling strategies and the use of conditioning in model building, while also presenting an overview of both classical statistical inference and Bayesian statistical inference.