A First Course in Probability (8th Edition)

A First Course in Probability (Eighth Edition)
By Sheldon Ross

Features clear and intuitive explanations of the mathematics of probability theory, outstanding problem sets, and a wide variety of diverse examples and applications, ideal for an upper-level undergraduate or graduate-level introduction to probability for math, science, engineering, and business students. Ross's concise writing style and refined textual organization cover conditional probability and independence of events, conditioning, expectation, and discrete, continuous, and jointly distributed random variables with unparalleled clarity, reinforced throughout by interesting exercises and numerous worked examples. Fundamental concepts such as the principles of combinatorial analysis — key to computing probabilities — and the axioms of probability theory are thoroughly covered early on, giving students a solid foundation before moving into more advanced topics. This eighth edition continues the evolution and fine-tuning of the text, adding new problems, exercises, and material chosen both for inherent interest and for building genuine intuition about probability, alongside a key structural change: the important result that the expectation of a sum of random variables equals the sum of the expectations is now introduced earlier, in Chapter 4, rather than Chapter 7 as in previous editions.

Topics commonly covered include:

• Combinatorial analysis
• Axioms of probability
• Conditional probability and independence
• Random variables and expectation
• Special random variables (Binomial, Poisson, Normal, etc.)
• Distributions of sampling statistics
• Conditioning
• Additional topics (Markov chains, the Poisson process, information and coding theory)
• Simulation

Key features:

• Three sets of end-of-chapter exercises — Problems, Theoretical Exercises, and Self-Test Problems and Exercises — the last with complete solutions for exam preparation
• Earlier introduction of the sum-of-expectations result for improved conceptual flow
• Assumes only a background in elementary calculus
• New examples added for building intuition, such as knockout tournament and gambler's ruin problems
• Long-standing, widely used standard text across math, science, engineering, and business probability courses

Perfect for:

• Upper-level undergraduate students taking their first probability course
• Graduate students in math, science, engineering, or business needing a probability foundation
• Students preparing for actuarial or statistics-heavy coursework
• Faculty teaching a rigorous, example-rich introductory probability course

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