Probability Theory for Quantitative Scientists
Published on 14. August 2025
Book
Hardback
432 pages
978-1-009-58069-4 (ISBN)
Description
Based on the long-running Probability Theory course at the Sapienza University of Rome, this book offers a fresh and in-depth approach to probability and statistics, while remaining intuitive and accessible in style. The fundamentals of probability theory are elegantly presented, supported by numerous examples and illustrations, and modern applications are later introduced giving readers an appreciation of current research topics. The text covers distribution functions, statistical inference and data analysis, and more advanced methods including Markov chains and Poisson processes, widely used in dynamical systems and data science research. The concluding section, 'Entropy, Probability and Statistical Mechanics' unites key concepts from the text with the authors' impressive research experience, to provide a clear illustration of these powerful statistical tools in action. Ideal for students and researchers in the quantitative sciences this book provides an authoritative account of probability theory, written by leading researchers in the field.
Reviews / Votes
'An outstanding book on probability, masterfully written by world-leading experts in the field. Both accessible and profound, it is destined to become a classic for physicists and quantitative scientists alike.' Ginestra Bianconi, Queen Mary University of London 'The book is a fascinating distillation of much of the useful parts of probability and statistics, with brilliant insights woven throughout. The connections drawn between statistical physics, the Fokker-Planck and Schrodinger equations are mind blowing.' Persi Diaconis, Stanford University 'Here, at last, is a book that strikes the right balance between a solid presentation of probability theory and examples of advanced developments in various fields of science...this is a must read for anyone who wants to understand the use of probability in data analysis, statistical inference, or stochastic processes, as well as its deep connections to statistical physics.' Marc Mezard, Bocconi UniversityMore details
Language
English
Place of publication
Cambridge
United Kingdom
Illustrations
Worked examples or Exercises
Dimensions
Height: 261 mm
Width: 185 mm
Thickness: 26 mm
Weight
1052 gr
ISBN-13
978-1-009-58069-4 (9781009580694)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
Luca Leuzzi is CNR Senior Researcher at the Institute of Nanotechnology (CNR-NANOTEC) in Italy. His research focuses on disordered systems and complex photonics. He has taught undergraduate courses in probability theory, computational physics, the theory of stochastic processes, statistical physics, and machine learning at Sapienza University of Rome.
Content
1. Introduction to probability; 2. Probability distributions; 3. Law of large numbers and central limit theorem; 4. Large deviations; 5. Statistical inference and experimental data analysis; 6. Multivariate and correlated experimental data; 7. Random walkers; 8. Generating functions and chain reactions; 9. Recurrent events; 10. Markov chains; 11. Numerical simulations; 12. Correlated events; 13. Continuous time Markov processes; 14. Entropy, Probability, Statistical Mechanics.