<b>INTRODUCTION TO PROBABILITY</b> <p><b>Discover practical models and real-world applications of multivariate models useful in engineering, business, and related disciplines</b> <p>In <i>Introduction to Probability: Multivariate Models and Applications, </i>a team of distinguished researchers delivers a comprehensive exploration of the concepts, methods, and results in multivariate distributions and models. Intended for use in a second course in probability, the material is largely self-contained, with some knowledge of basic probability theory and univariate distributions as the only prerequisite. <p>This textbook is intended as the sequel to<i> Introduction to Probability: Models and Applications.</i> Each chapter begins with a brief historical account of some of the pioneers in probability who made significant contributions to the field. It goes on to describe and explain a critical concept or method in multivariate models and closes with two collections of exercises designed to test basic and advanced understanding of the theory. <p>A wide range of topics are covered, including joint distributions for two or more random variables, independence of two or more variables, transformations of variables, covariance and correlation, a presentation of the most important multivariate distributions, generating functions and limit theorems. This important text: <ul><li>Includes classroom-tested problems and solutions to probability exercises </li> <li>Highlights real-world exercises designed to make clear the concepts presented </li> <li>Uses Mathematica software to illustrate the text’s computer exercises</li> <li>Features applications representing worldwide situations and processes </li> <li>Offers two types of self-assessment exercises at the end of each chapter, so that students may review the material in that chapter and monitor their progress</li></ul> <p>Perfect for students majoring in statistics, engineering, business, psychology, operations research and mathematics taking a second course in probability, <i>Introduction to Probability: Multivariate Models and Applications</i> is also an indispensable resource for anyone who is required to use multivariate distributions to model the uncertainty associated with random phenomena.

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# Introduction to Probability

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Multivariate Models and Applications

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