Probability theory : an introductory course
著者
書誌事項
Probability theory : an introductory course
（Springer textbook）
Springer-Verlag, c1992
- : gw
- : us
- タイトル別名
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Kurs teorii veroyatnostej
Курс теории вероятностей
Kurs teorii veroi︠a︡tnosteĭ
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注記
"Title of the Russian original edition (in two parts) : Kurs teorii veroyatnostej, Publisher MGU, 1985 and 1986"--T.p. verso
内容説明・目次
- 巻冊次
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: us ISBN 9780387533483
内容説明
Leads the student through the standard material for probability theory, with stops along the way for interesting topics such as statistical mechanics, not usually covered in a book for beginners. Covers independent identical trials and the law of large numbers, De Moivre-Laplace and Poisson limit th
- 巻冊次
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: gw ISBN 9783540533481
内容説明
Sinai's book leads the student through the standard materialfor ProbabilityTheory, with stops along the way forinteresting topics such as statistical mechanics, notusually included in a book for beginners.The first part of the book covers discrete random variables,using the same approach, basedon Kolmogorov's axioms forprobability, used later for the general case.The text is divided into sixteen lectures, each covering amajor topic. The introductory notions and classical resultsare included, of course: random variables, the central limittheorem, the law of large numbers, conditional probability,random walks, etc. Sinai's style is accessible and clear,with interesting examples to accompany new ideas.Besides statistical mechanics, other interesting, lesscommon topics found in the book are: percolation, theconcept of stability in the central limit theorem and thestudy of probability of large deviations.Little more than a standard undergraduate course in analysisis assumed of the reader. Notions from measure theory andLebesgue integration are introduced in the second half ofthe text.The book is suitable for second or third year students inmathematics, physics or other natural sciences.
It couldalso be usedby more advanced readers who want to learn themathematics of probability theory and some of itsapplications in statistical physics.
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