Exercises in Probability: A Guided Tour from Measure Theory to Random Processes, via Conditioning (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 13)

L., Chaumont M. Yor:

ISBN 10: 0521825857 / ISBN 13: 9780521825856

Edité par Cambridge University Press 01.2004., 2004

A propos de cet article

184 Seiten Gutes Exemplar, geringe Gebrauchsspuren, Cover/SU berieben/bestoßen, innen alles in Ordnung; Good copy, light signs of previous use, cover/dust jacket shows some rubbing/wear, interior in good condition D231223axu35 ISBN: 9780521825856 Sprache: Englisch Gewicht in Gramm: 598.

N° de réf. du vendeur 677901

Détails bibliographiques

• Titre: Exercises in Probability: A Guided Tour from Measure Theory to Random Processes, via Conditioning (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 13)
• Éditeur: Cambridge University Press 01.2004.
• Date de parution: 2004
• Langue: anglais
• ISBN à 10 chiffres: 0521825857
• ISBN à 13 chiffres: 9780521825856
• Reliure: hardcover
• État de l'article: Gut

A propos de ce titre

Synopsis

Exercises in advanced probability with solutions, references and contextual notes. Fully class tested in Paris.

Présentation de l'éditeur

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.