Measure-Theoretic Probability: With Applications to Statistics, Finance, and Engineering

By Kenneth Shum

This textbook offers an approachable introduction to measure-theoretic probability, illustrating core concepts with examples from statistics and engineering. The author presents complex concepts in a succinct manner, making otherwise intimidating material approachable to undergraduates who are not necessarily studying mathematics as their major. Throughout, readers will learn how probability serves as the language in a variety of exciting fields. Specific applications covered include the coupon collector's problem, Monte Carlo integration in finance, data compression in information theory, and more.

Measure-Theoretic Probability is ideal for a one-semester course and will best suit undergraduates studying statistics, data science, financial engineering, and economics who want to understand and apply more advanced ideas from probability to their disciplines. As a concise and rigorous introduction to measure-theoretic probability, it is also suitable for self-study.Prerequisites include a basic knowledge of probability and elementary concepts from real analysis.

• Format: Paperback
• Language: English
• ISBN: 3031498321
• ISBN13: 9783031498329
• Release Date: March 2024
• Publisher: Birkhauser
• Length: 259 Pages
• Weight: 0.90 lbs.
• Dimensions: 0.7" x 6.2" x 9.3"