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

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.

• | Author: Kenneth Shum
• | Publisher: Birkhauser
• | Publication Date: Mar 31, 2024
• | Number of Pages: 259 pages
• | Binding: Paperback or Softback
• | ISBN-10: 3031498321
• | ISBN-13: 9783031498329