Elementary Probability
The Ideas Before the Theory
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Beschreibung
This book provides a complete one-semester introduction to probability, combining intuition, rigorous analysis, and numerical methods. A key feature of the book is its numerous exercises, which encourage learning by doing. About half of these exercises are accompanied by detailed solutions, making the book suitable for self-study.
The topics covered include the standard material for such courses: combinatorics, discrete and continuous models, and the convergence of random variables and distributions. An additional chapter is devoted to Markov chains and their applications.
The target audience consists of second-year students in engineering, information sciences, economics, and mathematics. The mathematical level is kept accessible, while fostering connections with related topics that students may have encountered in other courses.
This book provides a complete one-semester introduction to probability, combining intuition, rigorous analysis, and numerical methods. A key feature of the book is its numerous exercises, which encourage learning by doing. About half of these exercises are accompanied by detailed solutions, making the book suitable for self-study.
The topics covered include the standard material for such courses: combinatorics, discrete and continuous models, and the convergence of random variables and distributions. An additional chapter is devoted to Markov chains and their applications.
The target audience consists of second-year students in engineering, information sciences, economics, and mathematics. The mathematical level is kept accessible, while fostering connections with related topics that students may have encountered in other courses.
Integrates intuition, rigorous computations, and numerical aspects Includes numerous exercises with detailed solutions Aimed at introductory courses Additional content is available on chapter level
Autor*in
Paolo Baldi
Themen in »Elementary Probability«
Combinatorics Main discrete and continuous distributions Computation of laws Introduction to modeling Simulation Markov chains The Metropolis algorithm First hints in statistics