Measure-Theoretic Probability
Produktnummer:
1875d10e757ef949058b9f36b7979b27dd
Autor: | Shum, Kenneth |
---|---|
Themengebiete: | Borel-Cantelli lemmas Measure-theoretic probability Measure theory Probability applications Probability theory Random variables Real analysis Riemann-Stieltjes integral Sigma fields Statistical independence |
Veröffentlichungsdatum: | 31.03.2024 |
EAN: | 9783031498329 |
Sprache: | Englisch |
Seitenzahl: | 259 |
Produktart: | Kartoniert / Broschiert |
Verlag: | Springer International Publishing |
Untertitel: | With Applications to Statistics, Finance, and Engineering |
Produktinformationen "Measure-Theoretic Probability"
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.

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