From the reviews: "Throughout the book, the author chooses examples and exercises that are classics in the field of probability ... . does an admirable job of combining the rigor necessary for a first course in probability theory while continuing to engage the more applied oriented student's curiosity with interesting examples and exercises. The book deserves serious consideration for anyone teaching the first course in probability theory or one engaged in applied work who desires a more thorough grounding in the mathematical principles of probability theory." (Mark A. Mccomb, Technometrics, Vol. 54 (1), February, 2012) "The present book is a text on the fundamentals of probability at an undergraduate and first-year graduate level for students in science, engineering and economics. ... The book has an excellent set of examples and exercises and two appendices on supplementary homework, practice problems, symbols and formulas." (Andreas N. Philippou, Zentralblatt MATH, Vol. 1211, 2011)

• Introducing Probability.- The Birthday and Matching Problems.- Conditional Probability and Independence.- Integer-Valued and Discrete Random Variables.- Generating Functions.- Standard Discrete Distributions.- Continuous Random Variables.- Some Special Continuous Distributions.- Normal Distribution.- Normal Approximations and the Central Limit Theorem.- Multivariate Discrete Distributions.- Multidimensional Densities.- Convolutions and Transformations.- Markov Chains and Applications.- Urn Models in Physics and Genetics.

From the reviews: "Throughout the book, the author chooses examples and exercises that are classics in the field of probability ... . does an admirable job of combining the rigor necessary for a first course in probability theory while continuing to engage the more applied oriented student's curiosity with interesting examples and exercises. The book deserves serious consideration for anyone teaching the first course in probability theory or one engaged in applied work who desires a more thorough grounding in the mathematical principles of probability theory." (Mark A. Mccomb, Technometrics, Vol. 54 (1), February, 2012) "The present book is a text on the fundamentals of probability at an undergraduate and first-year graduate level for students in science, engineering and economics. ... The book has an excellent set of examples and exercises and two appendices on supplementary homework, practice problems, symbols and formulas." (Andreas N. Philippou, Zentralblatt MATH, Vol. 1211, 2011)

• Introducing Probability.- The Birthday and Matching Problems.- Conditional Probability and Independence.- Integer-Valued and Discrete Random Variables.- Generating Functions.- Standard Discrete Distributions.- Continuous Random Variables.- Some Special Continuous Distributions.- Normal Distribution.- Normal Approximations and the Central Limit Theorem.- Multivariate Discrete Distributions.- Multidimensional Densities.- Convolutions and Transformations.- Markov Chains and Applications.- Urn Models in Physics and Genetics.

From the reviews: "Throughout the book, the author chooses examples and exercises that are classics in the field of probability ... . does an admirable job of combining the rigor necessary for a first course in probability theory while continuing to engage the more applied oriented student's curiosity with interesting examples and exercises. The book deserves serious consideration for anyone teaching the first course in probability theory or one engaged in applied work who desires a more thorough grounding in the mathematical principles of probability theory." (Mark A. Mccomb, Technometrics, Vol. 54 (1), February, 2012) "The present book is a text on the fundamentals of probability at an undergraduate and first-year graduate level for students in science, engineering and economics. ... The book has an excellent set of examples and exercises and two appendices on supplementary homework, practice problems, symbols and formulas." (Andreas N. Philippou, Zentralblatt MATH, Vol. 1211, 2011)

• Introducing Probability.- The Birthday and Matching Problems.- Conditional Probability and Independence.- Integer-Valued and Discrete Random Variables.- Generating Functions.- Standard Discrete Distributions.- Continuous Random Variables.- Some Special Continuous Distributions.- Normal Distribution.- Normal Approximations and the Central Limit Theorem.- Multivariate Discrete Distributions.- Multidimensional Densities.- Convolutions and Transformations.- Markov Chains and Applications.- Urn Models in Physics and Genetics.