A Second Course in Probability (Paperback)

Sheldon M. Ross

ISBN 10: 1009179918 / ISBN 13: 9781009179911

Published by Cambridge University Press, Cambridge, 2023

About this Item

Paperback. Written by Sheldon Ross and Erol Pekoez, this text familiarises you with advanced topics in probability while keeping the mathematical prerequisites to a minimum. Topics covered include measure theory, limit theorems, bounding probabilities and expectations, coupling and Stein's method, martingales, Markov chains, renewal theory, and Brownian motion. No other text covers all these topics rigorously but at such an accessible level - all you need is an undergraduate-level understanding of calculus and probability. New to this edition are sections on the gambler's ruin problem, Stein's method as applied to exponential approximations, and applications of the martingale stopping theorem. Extra end-of-chapter exercises have also been added, with selected solutions available.This is an ideal textbook for students taking an advanced undergraduate or graduate course in probability. It also represents a useful resource for professionals in relevant application domains, from finance to machine learning. The second edition of this popular text explores advanced topics in probability while keeping mathematical prerequisites to a minimum. With copious exercises and examples, it is an ideal guide for graduate students and professionals in application domains that depend on probability, including operations research, finance and machine learning. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Seller Inventory # 9781009179911

Bibliographic Details

• Title: A Second Course in Probability (Paperback)
• Publisher: Cambridge University Press, Cambridge
• Publication Date: 2023
• Language: English
• ISBN 10: 1009179918
• ISBN 13: 9781009179911
• Binding: Paperback
• Edition: 2nd Edition
• Condition: new

About this title

Synopsis

Written by Sheldon Ross and Erol Peköz, this text familiarises you with advanced topics in probability while keeping the mathematical prerequisites to a minimum. Topics covered include measure theory, limit theorems, bounding probabilities and expectations, coupling and Stein's method, martingales, Markov chains, renewal theory, and Brownian motion. No other text covers all these topics rigorously but at such an accessible level - all you need is an undergraduate-level understanding of calculus and probability. New to this edition are sections on the gambler's ruin problem, Stein's method as applied to exponential approximations, and applications of the martingale stopping theorem. Extra end-of-chapter exercises have also been added, with selected solutions available.This is an ideal textbook for students taking an advanced undergraduate or graduate course in probability. It also represents a useful resource for professionals in relevant application domains, from finance to machine learning.

About the Authors

Sheldon M. Ross is the Epstein Chair Professor in the Epstein Department of Industrial and Systems Engineering at the University of Southern California. He has published more than 150 technical articles as well as a variety of textbooks in the areas of applied probability, statistics, and industrial engineering. He is the founding and continuing editor of the journal Probability in the Engineering and Informational Sciences, a fellow of the Institute of Mathematical Statistics and of the Institute for Operations Research and the Management Sciences, and a recipient of the Humboldt US Senior Scientist Award. He is the recipient of the 2006 INFORMS Expository Writing Award.

Erol A. Peköz is Professor and Department Chair of Operations and Technology Management in the Questrom School of Business at Boston University. He has published more than 50 technical articles in applied probability and statistics, and is the author of 'The Manager's Guide to Statistics' (2009). At Boston University, he was awarded the 2001 Broderick Prize for Teaching.