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Advances in Complex Function Theory (Lecture Notes in Mathematics) by W. E. Kirwan (Repost)
Matrix Mathematics - Theory, Facts, and Formulas, Second Edition
Mathematics Probability, Markov Chains, Queues, and Simulation - The Mathematical Basis of Performance Modeling
Algebraic Aspects of Cryptography (Algorithms and Computation in Mathematics) by Neal Koblitz (Repost)
Mathematics Mathematical Foundations of Computer Science 2004 [Repost]
Mathematics Mathematical Logic for Computer Science (3rd edition)
Spaces of Holomorphic Functions in the Unit Ball (Graduate Texts in Mathematics) by Kehe Zhu (Repost)
An Introduction to Ergodic Theory (Graduate Texts in Mathematics) by Peter Walters (Repost)
Mathematics Symmetry Theory in Molecular Physics with Mathematica: A new kind of tutorial book (Repost)
-Mathematics for the Physical Sciences- by Herbert S. Wilf
Mathematics for Elementary Teachers - A Conceptual Approach, 9 edition
Computer-Enabled Mathematics - Integrating Experiment and Theory in Teacher Education
How to Fold It - The Mathematics of Linkages, Origami and Polyhedra
Mathematics Engineering Analysis: Interactive Methods and Programs with FORTRAN, QuickBASIC, MATLAB, and Mathematica [Repost]
Mathematics Maverick Mathematician: The Life and Science of J.E. Moyal
African Mathematics: From Bones to Computers (repost)
Topology (Allyn and Bacon Series in Advanced Mathematics) by James Dugundji
Mathematics Fundamentals of Algebraic Modeling - An Introduction to Mathematical Modeling with Algebra and Statistics, 5 edition
Mathematics LMSST - 24 Lectures on Elliptic Curves (London Mathematical Society Student Texts) by J. W. S. Cassels
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Discrete Probability (Undergraduate Texts in Mathematics)
Posted on 2010-04-13
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Author: Hugh Gordon
Publisher: Springer (1997) Binding: Hardcover, 284 pages pricer: $59.95 ISBN-10: 0387982272 editorialreviews 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. checked checked
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