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9789812703712: First Look At Rigorous Probability Theory, A (2Nd Edition)

Synopsis

“This is a fine textbook on probability theory based on measure theory. The parts of measure theory that are needed are developed within the book and a teacher of measure theory could find them quite useful. The construction of the Lebesgue measure (extension theorem) is unusual and interesting.” Mathematical Reviews “This short, lucid and excellent textbook should be a required course for all graduate students of mathematics and statistics as well as for interested graduate / PhD students in engineering, computer sciences, economics, and management who lack exposure to measure theoretic applications in probability theory.” Professor B K Sahu Indian Institute of Technology, India Solutions Manual for Free Download This textbook is an introduction to probability theory using measure theory. It is designed for graduate students in a variety of fields (mathematics, statistics, economics, management, finance, computer science, and engineering) who require a working knowledge of probability theory that is mathematically precise, but without excessive technicalities. The text provides complete proofs of all the essential introductory results. Nevertheless, the treatment is focused and accessible, with the measure theory and mathematical details presented in terms of intuitive probabilistic concepts, rather than as separate, imposing subjects. In this new edition, many exercises and small additional topics have been added and existing ones expanded. The text strikes an appropriate balance, rigorously developing probability theory while avoiding unnecessary detail.

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Présentation de l'éditeur

“This is a fine textbook on probability theory based on measure theory. The parts of measure theory that are needed are developed within the book and a teacher of measure theory could find them quite useful. The construction of the Lebesgue measure (extension theorem) is unusual and interesting.” Mathematical Reviews “This short, lucid and excellent textbook should be a required course for all graduate students of mathematics and statistics as well as for interested graduate / PhD students in engineering, computer sciences, economics, and management who lack exposure to measure theoretic applications in probability theory.” Professor B K Sahu Indian Institute of Technology, India Solutions Manual for Free Download This textbook is an introduction to probability theory using measure theory. It is designed for graduate students in a variety of fields (mathematics, statistics, economics, management, finance, computer science, and engineering) who require a working knowledge of probability theory that is mathematically precise, but without excessive technicalities. The text provides complete proofs of all the essential introductory results. Nevertheless, the treatment is focused and accessible, with the measure theory and mathematical details presented in terms of intuitive probabilistic concepts, rather than as separate, imposing subjects. In this new edition, many exercises and small additional topics have been added and existing ones expanded. The text strikes an appropriate balance, rigorously developing probability theory while avoiding unnecessary detail.

Revue de presse

This is a fine textbook on probability theory based on measure theory. The parts of measure theory that are needed are developed within the book and a teacher of measure theory could find them quite useful. The construction of the Lebesgue measure (extension theorem) is unusual and interesting. --Mathematical Reviews

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9789812703705: A First Look at Rigorous Probability Theory

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ISBN 10 :  9812703705 ISBN 13 :  9789812703705
Editeur : World Scientific Publishing Co P..., 2006
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Paperback. Etat : New. This textbook is an introduction to probability theory using measure theory. It is designed for graduate students in a variety of fields (mathematics, statistics, economics, management, finance, computer science, and engineering) who require a working knowledge of probability theory that is mathematically precise, but without excessive technicalities. The text provides complete proofs of all the essential introductory results. Nevertheless, the treatment is focused and accessible, with the measure theory and mathematical details presented in terms of intuitive probabilistic concepts, rather than as separate, imposing subjects. In this new edition, many exercises and small additional topics have been added and existing ones expanded. The text strikes an appropriate balance, rigorously developing probability theory while avoiding unnecessary detail. N° de réf. du vendeur LU-9789812703712

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Paperback. Etat : New. This textbook is an introduction to probability theory using measure theory. It is designed for graduate students in a variety of fields (mathematics, statistics, economics, management, finance, computer science, and engineering) who require a working knowledge of probability theory that is mathematically precise, but without excessive technicalities. The text provides complete proofs of all the essential introductory results. Nevertheless, the treatment is focused and accessible, with the measure theory and mathematical details presented in terms of intuitive probabilistic concepts, rather than as separate, imposing subjects. In this new edition, many exercises and small additional topics have been added and existing ones expanded. The text strikes an appropriate balance, rigorously developing probability theory while avoiding unnecessary detail. N° de réf. du vendeur LU-9789812703712

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Etat : New. Features an introduction to probability theory using measure theory. This work provides proofs of the essential introductory results and presents the measure theory and mathematical details in terms of intuitive probabilistic concepts, rather than as separate, imposing subjects. Num Pages: 236 pages, Illustrations. BIC Classification: PBT. Category: (P) Professional & Vocational. Dimension: 227 x 153 x 16. Weight in Grams: 430. . 2006. 2nd Edition. Paperback. . . . . N° de réf. du vendeur V9789812703712

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