Theory of Probability Explorations and Applications

ISBN-10: 1107024471

ISBN-13: 9781107024472

Edition: 2012

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Description: From classical foundations to advanced modern theory, this self-contained and comprehensive guide to probability weaves together mathematical proofs, historical context and richly detailed illustrative applications. A theorem discovery approach is used throughout, setting each proof within its historical setting and is accompanied by a consistent emphasis on elementary methods of proof. Each topic is presented in a modular framework, combining fundamental concepts with worked examples, problems and digressions which, although mathematically rigorous, require no specialised or advanced mathematical background. Augmenting this core material are over 80 richly embellished practical applications of probability theory, drawn from a broad spectrum of areas both classical and modern, each tailor-made to illustrate the magnificent scope of the formal results. Providing a solid grounding in practical probability, without sacrificing mathematical rigour or historical richness, this insightful book is a fascinating reference and essential resource, for all engineers, computer scientists and mathematicians.

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Book details

List price: $62.00
Copyright year: 2012
Publisher: Cambridge University Press
Publication date: 11/8/2012
Binding: Hardcover
Pages: 827
Size: 6.75" wide x 9.75" long x 1.75" tall
Weight: 4.114
Language: English

Santosh S. Venkatesh is an Associate Professor of Electrical and Systems Engineering at the University of Pennsylvania, whose research interests include probability, information, communication and learning theory, pattern recognition, computational neuroscience, epidemiology and computer security. He is a member of the David Mahoney Institute for Neurological Sciences and has been awarded the Lindback Award for Distinguished Teaching.

Elements
Probability spaces
Conditional probability
A first look at independence
Probability sieves
Numbers play a game of chance
The normal law
Probabilities on the real line
The Bernoulli schema
The essence of randomness
The coda of the normal
Foundations
Distribution functions and measure
Random variables
Great expectations
Variations on a theme of integration
Laplace transforms
The law of large numbers
From inequalities to concentration
Poisson approximation
Convergence in law, selection theorems
Normal approximation
Appendices
Sequences, functions, spaces
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