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Chemical Dynamics in Condensed PhasesRelaxation, Transfer and Reactions in Condensed Molecular Systems$
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Abraham Nitzan

Print publication date: 2006

Print ISBN-13: 9780198529798

Published to Oxford Scholarship Online: November 2020

DOI: 10.1093/oso/9780198529798.001.0001

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PRINTED FROM OXFORD SCHOLARSHIP ONLINE (oxford.universitypressscholarship.com). (c) Copyright Oxford University Press, 2021. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in OSO for personal use. date: 05 December 2021

Review Of Some Mathematical And Physical Subjects

Review Of Some Mathematical And Physical Subjects

Chapter:
(p.3) 1 Review Of Some Mathematical And Physical Subjects
Source:
Title Pages
Author(s):

Abraham Nitzan

Publisher:
Oxford University Press
DOI:10.1093/oso/9780198529798.003.0006

This chapter reviews some subjects in mathematics and physics that are used in different contexts throughout this book. The selection of subjects and the level of their coverage reflect the author’s perception of what potential users of this text were exposed to in their earlier studies. Therefore, only brief overview is given of some subjects while somewhat more comprehensive discussion is given of others. In neither case can the coverage provided substitute for the actual learning of these subjects that are covered in detail by many textbooks. A random variable is an observable whose repeated determination yields a series of numerical values (“realizations” of the random variable) that vary from trial to trial in a way characteristic of the observable. The outcomes of tossing a coin or throwing a die are familiar examples of discrete random variables. The position of a dust particle in air and the lifetime of a light bulb are continuous random variables. Discrete random variables are characterized by probability distributions; Pn denotes the probability that a realization of the given random variable is n. Continuous random variables are associated with probability density functions P(x): P(x1)dx denotes the probability that the realization of the variable x will be in the interval x1 . . . x1+dx.

Keywords:   Cauchy theorem, Debye-Huckel theory, Gauss law, Heavyside step function, Lagrange multipliers, Poisson brackets, Schwarz inequality, binomial distribution, canonical ensemble

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