img Leseprobe Leseprobe

Probability Theory

Y. A. Rozanov

EPUB
15,54
Amazon iTunes Thalia.de Weltbild.de Hugendubel Bücher.de ebook.de kobo Osiander Google Books Barnes&Noble bol.com Legimi yourbook.shop Kulturkaufhaus ebooks-center.de
* Affiliatelinks/Werbelinks
Hinweis: Affiliatelinks/Werbelinks
Links auf reinlesen.de sind sogenannte Affiliate-Links. Wenn du auf so einen Affiliate-Link klickst und über diesen Link einkaufst, bekommt reinlesen.de von dem betreffenden Online-Shop oder Anbieter eine Provision. Für dich verändert sich der Preis nicht.

Dover Publications img Link Publisher

Naturwissenschaften, Medizin, Informatik, Technik / Mathematik

Beschreibung

This book, a concise introduction to modern probability theory and certain of its ramifications, deals with a subject indispensable to natural scientists and mathematicians alike. Here the readers, with some knowledge of mathematics, will find an excellent treatment of the elements of probability together with numerous applications. Professor Y. A. Rozanov, an internationally known mathematician whose work in probability theory and stochastic processes has received wide acclaim, combines succinctness of style with a judicious selection of topics. His book is highly readable, fast-moving, and self-contained.The author begins with basic concepts and moves on to combination of events, dependent events and random variables. He then covers Bernoulli trials and the De Moivre-Laplace theorem, which involve three important probability distributions (binomial, Poisson, and normal or Gaussian). The last three chapters are devoted to limit theorems, a detailed treatment of Markov chains, continuous Markov processes. Also included are appendixes on information theory, game theory, branching processes, and problems of optimal control. Each of the eight chapters and four appendixes has been equipped with numerous relevant problems (150 of them), many with hints and answers. This volume is another in the popular series of fine translations from the Russian by Richard A. Silverman. Dr. Silverman, a former member of the Courant Institute of Mathematical Sciences of New York University and the Lincoln Laboratory of the Massachusetts Institute of Technology, is himself the author of numerous papers on applied probability theory. He has heavily revised the English edition and added new material. The clear exposition, the ample illustrations and problems, the cross-references, index, and bibliography make this book useful for self-study or the classroom.

Weitere Titel in dieser Kategorie
Cover Quantum Leaps
Hugh Barker

Kundenbewertungen

Schlagwörter

books on distributions, books on introductory texts, crucial, distributions, books on exercises, books on matlab, combinatorial, books on processes, partitions, pleasant memories, books on functions, books on bulmers, books on odd times, books on lemmas, statistical probability, mathematics, books on mathematical statistics, bulmer, matlab, books on combinatorics, books on inferences, books on standard deviations, books on theorems, lemmas, poisson, books on advanced concepts, books on feller, books on variances, abstract algebra, advanced concepts, functions, exercises, feller, calculus, binomial, books on optimal controls, generate, books on liberal arts, books on variables, anova, liberal arts, books on proofs, branching, combinatorics, wait awhile, books on probabilities, variables, books on self-studies, primitive roots, books on partitions, generating, books on statistical probabilities, inductive, self-study, equations, regression, books on abstract algebras, theorems, russian, books on calculus, optimal control, theory class, chapter 8, books on equations, quadratic, books on poisson, education majors, odd times, books on fundamentals, fundamentals, processes, proofs, probabilities, books on education majors, books on mathematics, books on normal distributions, waiting awhile, books on theory classes, variance, books on anova, stochastic, books on regressions, introductory text, inference, mathematical statistics, standard deviation, normal distribution, one-semester