Introduction to Probability with Texas Hold’em Examples

Schoenberg, Frederic Paik

ISBN 10: 1439827680 / ISBN 13: 9781439827680

Published by Chapman and Hall/CRC, 2011

About this Item

Condition: Good. Ex-university library copy with associated library stamps etc. Soft cover, no jacket. 189pp. No highlighting or annotations to text. Covered in protective laminate. Photo on request.

Seller Inventory # 943879

Bibliographic Details

• Title: Introduction to Probability with Texas Hold?em Examples
• Publisher: Chapman and Hall/CRC
• Publication Date: 2011
• Language: English
• ISBN 10: 1439827680
• ISBN 13: 9781439827680
• Binding: Soft cover
• Condition: Good
• Dust Jacket Condition: No Jacket

About this title

Synopsis

Introduction to Probability with Texas Hold’em Examples illustrates both standard and advanced probability topics using the popular poker game of Texas Hold’em, rather than the typical balls in urns. The author uses students’ natural interest in poker to teach important concepts in probability.

This classroom-tested book covers the main subjects of a standard undergraduate probability course, including basic probability rules, standard models for describing collections of data, and the laws of large numbers. It also discusses several more advanced topics, such as the ballot theorem, the arcsine law, and random walks, as well as some specialized poker issues, such as the quantification of luck and skill in Texas Hold’em. Homework problems are provided at the end of each chapter.

The author includes examples of actual hands of Texas Hold’em from the World Series of Poker and other major tournaments and televised games. He also explains how to use R to simulate Texas Hold’em tournaments for student projects. R functions for running the tournaments are freely available from CRAN (in a package called holdem).

See Professor Schoenberg discuss the book.

About the Author

Frederic Paik Schoenberg is a professor and graduate vice-chair of statistics at UCLA. He is also co-editor of the Journal of Environmental Statistics. He earned a Ph.D. in statistics from UC Berkeley. His research interests include point processes, image analysis, time series, and applications in seismology and fire ecology.