Probability Theory for Quantitative Scientists
Cambridge University Press (Verlag)
978-1-009-58069-4 (ISBN)
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.
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. Enzo Marinari is a Professor of Theoretical Physics at the Sapienza University of Rome, renowned for his contributions to statistical mechanics and condensed matter theory. Over decades, he has taught numerous courses at Sapienza, including probability theory, computational physics, and statistical mechanics. Giorgio Parisi is Professor Emeritus of Theoretical Physics at Sapienza University of Rome and is widely regarded as one of the leading theoretical physicists of our time. He has made seminal contributions to both statistical physics and condensed matter physics, earning him the Nobel Prize in Physics in 2021. Parisi was also awarded the prestigious Wolf Prize in 2021 for his groundbreaking discoveries in disordered systems, particle physics, and statistical physics.
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.
| Erscheinungsdatum | 15.08.2025 |
|---|---|
| Zusatzinfo | Worked examples or Exercises |
| Verlagsort | Cambridge |
| Sprache | englisch |
| Maße | 183 x 259 mm |
| Gewicht | 1050 g |
| Themenwelt | Mathematik / Informatik ► Mathematik ► Angewandte Mathematik |
| Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik | |
| Naturwissenschaften ► Physik / Astronomie ► Angewandte Physik | |
| ISBN-10 | 1-009-58069-8 / 1009580698 |
| ISBN-13 | 978-1-009-58069-4 / 9781009580694 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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