Probability Theory
A Comprehensive Course
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Beschreibung
This popular textbook, now in a revised and expanded third edition, presents a comprehensive course in modern probability theory.
Probability plays an increasingly important role not only in mathematics, but also in physics, biology, finance and computer science, helping to understand phenomena such as magnetism, genetic diversity and market volatility, and also to construct efficient algorithms. Starting with the very basics, this textbook covers a wide variety of topics in probability, including many not usually found in introductory books, such as:
- limit theorems for sums of random variables
- martingales
- percolation
- Markov chains and electrical networks
- construction of stochastic processes
- Poisson point process and infinite divisibility
- large deviation principles and statistical physics
- Brownian motion
- stochastic integrals and stochastic differential equations.
This third edition has been carefully extended and includes new features, such as concise summaries at the end of each section and additional questions to encourage self-reflection, as well as updates to the figures and computer simulations. With a wealth of examples and more than 290 exercises, as well as biographical details of key mathematicians, it will be of use to students and researchers in mathematics, statistics, physics, computer science, economics and biology.
This popular textbook, now in a revised and expanded third edition, presents a comprehensive course in modern probability theory.
Probability plays an increasingly important role not only in mathematics, but also in physics, biology, finance and computer science, helping to understand phenomena such as magnetism, genetic diversity and market volatility, and also to construct efficient algorithms. Starting with the very basics, this textbook covers a wide variety of topics in probability, including many not usually found in introductory books, such as:
- limit theorems for sums of random variables
- martingales
- percolation
- Markov chains and electrical networks
- construction of stochastic processes
- Poisson point process and infinite divisibility
- large deviation principles and statistical physics
- Brownian motion
- stochastic integrals and stochastic differential equations.
This third edition has been carefully extended and includes new features, such as concise summaries at the end of each section and additional questions to encourage self-reflection, as well as updates to the figures and computer simulations. With a wealth of examples and more than 290 exercises, as well as biographical details of key mathematicians, it will be of use to students and researchers in mathematics, statistics, physics, computer science, economics and biology.
Provides a complete introduction to probability theory, including measure theory and scientific applications New updated edition includes concise summaries of each section, as well as outlooks and questions in the text Clearly written to make complicated mathematics accessible
Autor*in
Achim Klenke
Themen in »Probability Theory«
Central Limit Theorem Markov Chain Martingales Stochastic Processes Stochastic Differential Equations Stochastic Integration Percolation Brownian Motion Poisson Point Process Measure Theory Integration Theory