Probability for Physicists
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Beschreibung
This book is designed as a practical and intuitive introduction to probability, statistics and random quantities for physicists. The book aims at getting to the main points by a clear, hands-on exposition supported by well-illustrated and worked-out examples. A strong focus on applications in physics and other natural sciences is maintained throughout. In addition to basic concepts of random variables, distributions, expected values and statistics, the book discusses the notions of entropy, Markov processes, and fundamentals of random number generation and Monte-Carlo methods.
This book is designed as a practical and intuitive introduction to probability, statistics and random quantities for physicists. The book aims at getting to the main points by a clear, hands-on exposition supported by well-illustrated and worked-out examples. A strong focus on applications in physics and other natural sciences is maintained throughout. In addition to basic concepts of random variables, distributions, expected values and statistics, the book discusses the notions of entropy, Markov processes, and fundamentals of random number generation and Monte-Carlo methods.
Gives a quick and intuitive introduction to the key concepts of probability, statistics and randomness Covers the basics of entropy, Markov processes, Monte-Carlo methods and stochastic population modeling Supported by illustrative, physics-focused examples Includes elaborate, fully solved end-of-chapter problems Includes supplementary material: sn.pub/extras
Autor*in
Simon Širca
Themen in »Probability for Physicists«
Entropy of physical systems Generation of pseudorandom numbers Markov processes Monte Carlo method Probability distributions Probability theory in physics Random variables and processes Regression calculations Statistical tests Stochastic population modeling
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“Širca … provides a thorough background; sections cover fundamentals of probability analysis, statistical distributions, and applications of the theories using computer-based algorithms. … The work includes useful graphs, four appendixes covering random number generation, and tables of normal distributions. There are extensive references and a valuable index. Summing Up: Recommended. Graduate students; researchers/faculty; professionals.” (N. Sadanand, Choice, Vol. 54 (4), December, 2016)
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