Discrete Probability

Beschreibung

DISCRETE PROBABILITY is a textbook, at a post-calculus level, for a first course in probability. Since continuous probability is not treated, discrete probability can be covered in greater depth. The result is a book of special interest to students majoring in computer science as well as those majoring in mathematics. Since calculus is used only occasionally, students who have forgotten calculus can nevertheless easily understand the book. The slow, gentle style and clear exposition will appeal to students. Basic concepts such as counting, independence, conditional probability, randon variables, approximation of probabilities, generating functions, random walks and Markov chains are presented with good explanation and many worked exercises. An important feature of the book is the abundance of problems, which students may use to master the material. The 1,196 numerical answers to the 405 exercises, many with multiple parts, are included at the end of the book. Throughout the book, various comments on the history of the study of probability are inserted. Biographical information about some of the famous contributors to probability such as Fermat, Pascal, the Bernoullis, DeMoivre, Bayes, Laplace, Poisson, Markov, and many others, is presented. This volume will appeal to a wide range of readers and should be useful in the undergraduate programs at many colleges and universities.
No knowledge of calculus required - Includes short biographical essays of some of the famous contributions to probability, including Fermat, Pascal, Laplace, Bayes, Bernoulli and Markov - The book comprises an abundance of 405 problems (with answers) to clarify topics.
"Discrete Probability" is an introductory textbook for a first course in probability theory. The book comprises a collection of 405 problems with answers at the end of the book. Half page long biographical essays give the reader insights in the lifes of such famous contributors to probability as Fermat, Pascal, Laplace, Bayes, Bernoulli, Stirling, Markov, and many others. A wide range of readers will enjoy this book and it should be useful in the undergraduate programs at many colleges and universities.

Autor*in

Hugh Gordon

Themen in »Discrete Probability«

Conditional probability Law of large numbers Markov chain Normal distribution Poisson distribution Random variable Variance random walk

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"The strength of the book are undoubtedly its exercises (over 400 of them), all with numerical solutions, and the many interesting remarks on the history of probability theory and biographies of important personalities that are scattered throughout the book."
European Mathematical Society Newsletter, December 2000
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