Exercises in Probability
A Guided Tour from Measure Theory to Random Processes, via Conditioning
- L. Chaumont, Université de Paris VI (Pierre et Marie Curie)
- M. Yor, Université de Paris VI (Pierre et Marie Curie)
This book was first published in 2003. Derived from extensive teaching experience in Paris, this book presents around 100 exercises in probability. The exercises cover measure theory and probability, independence and conditioning, Gaussian variables, distributional computations, convergence of random variables, and random processes. For each exercise the authors have provided detailed solutions as well as references for preliminary and further reading. There are also many insightful notes to motivate the student and set the exercises in context. Students will find these exercises extremely useful for easing the transition between simple and complex probabilistic frameworks. Indeed, many of the exercises here will lead the student on to frontier research topics in probability. Along the way, attention is drawn to a number of traps into which students of probability often fall. This book is ideal for independent study or as the companion to a course in advanced probability theory.Read more
- Class tested at the prestigious Paris school
- Draws attention to a number of traps that must be avoided by students of probability
- Includes detailed solutions to all exercises as well as references to the literature and contextual notes
Reviews & endorsements
Review of the hardback: 'In conclusion, this is an excellent book, which should be in every library, and also on the bookshelf of anyone with interests in advanced probability and random processes.' Society for Industrial and Applied MathematicsSee more reviews
Review of the hardback: '… extremely useful for graduate and postgraduate students and those who want to better understand advanced probability theory.' European Mathematical Society Newsletter
Review of the hardback: '… although the book could profitably be used as a companion to a graduate course in probability theory, it is probability best designed for the doctoral student who can read it alongside the source material. Used in that way, the book is a magnificent resource … consistency and clarity of mathematical style … For beginning researchers in stochastic mathematics, this book comes highly recommended and libraries should obtain a copy.' Journal of the Royal Statistical Society: Series A
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- Date Published: March 2011
- format: Adobe eBook Reader
- isbn: 9780511837807
- availability: This ISBN is for an eBook version which is distributed on our behalf by a third party.
Table of Contents
1. Measure theory and probability
2. Independence and conditioning
3. Gaussian variables
4. Distributional computations
5. Convergence of random variables
6. Random processes.
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