Ideal for students and researchers in the quantitative sciences, this book provides an authoritative and approachable account of probability theory, written by leading researchers in the field. Modern applications are also developed, giving readers an appreciation of important research topics such as statistical mechanics and information theory.
Ideal for students and researchers in the quantitative sciences, this book provides an authoritative and approachable account of probability theory, written by leading researchers in the field. Modern applications are also developed, giving readers an appreciation of important research topics such as statistical mechanics and information theory.
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.
Inhaltsangabe
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.
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.
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