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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Measure Theory and Probability Theory | Krishna B. Athreya (u. a.) | Taschenbuch | Springer Texts in Statistics | xviii | Englisch | 2010 | Humana | EAN 9781441921918 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book arose out of two graduate courses that the authors have taught duringthepastseveralyears;the rstonebeingonmeasuretheoryfollowed by the second one on advanced probability theory. The traditional approach to a rst course in measure theory, such as in Royden (1988), is to teach the Lebesgue measure on the real line, then the p di erentation theorems of Lebesgue, L -spaces on R, and do general m- sure at the end of the course with one main application to the construction of product measures. This approach does have the pedagogic advantage of seeing one concrete case rst before going to the general one. But this also has the disadvantage in making many students' perspective on m- sure theory somewhat narrow. It leads them to think only in terms of the Lebesgue measure on the real line and to believe that measure theory is intimately tied to the topology of the real line. As students of statistics, probability, physics, engineering, economics, and biology know very well, there are mass distributions that are typically nonuniform, and hence it is useful to gain a general perspective. This book attempts to provide that general perspective right from the beginning. The opening chapter gives an informal introduction to measure and integration theory. It shows that the notions of -algebra of sets and countable additivity of a set function are dictated by certain very na- ral approximation procedures from practical applications and that they are not just some abstract ideas.
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book arose out of two graduate courses that the authors have taught duringthepastseveralyears;the rstonebeingonmeasuretheoryfollowed by the second one on advanced probability theory. The traditional approach to a rst course in measure theory, such as in Royden (1988), is to teach the Lebesgue measure on the real line, then the p di erentation theorems of Lebesgue, L -spaces on R, and do general m- sure at the end of the course with one main application to the construction of product measures. This approach does have the pedagogic advantage of seeing one concrete case rst before going to the general one. But this also has the disadvantage in making many students' perspective on m- sure theory somewhat narrow. It leads them to think only in terms of the Lebesgue measure on the real line and to believe that measure theory is intimately tied to the topology of the real line. As students of statistics, probability, physics, engineering, economics, and biology know very well, there are mass distributions that are typically nonuniform, and hence it is useful to gain a general perspective. This book attempts to provide that general perspective right from the beginning. The opening chapter gives an informal introduction to measure and integration theory. It shows that the notions of -algebra of sets and countable additivity of a set function are dictated by certain very na- ral approximation procedures from practical applications and that they are not just some abstract ideas. 640 pp. Englisch.
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents the main concepts and results in measure theory and probability theory in a simple and easy-to-understand wayProvides heuristic explanations behind the theory to help students see the big pictureThis is a graduate level textboo.
Lingua: Inglese
Editore: Springer-Verlag New York Inc., 2010
ISBN 10: 1441921915 ISBN 13: 9781441921918
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book arose out of two graduate courses that the authors have taught duringthepastseveralyears;the rstonebeingonmeasuretheoryfollowed by the second one on advanced probability theory. The traditional approach to a rst course in measure theory, such as in Royden (1988), is to teach the Lebesgue measure on the real line, then the p di erentation theorems of Lebesgue, L -spaces on R, and do general m- sure at the end of the course with one main application to the construction of product measures. This approach does have the pedagogic advantage of seeing one concrete case rst before going to the general one. But this also has the disadvantage in making many students¿ perspective on m- sure theory somewhat narrow. It leads them to think only in terms of the Lebesgue measure on the real line and to believe that measure theory is intimately tied to the topology of the real line. As students of statistics, probability, physics, engineering, economics, and biology know very well, there are mass distributions that are typically nonuniform, and hence it is useful to gain a general perspective. This book attempts to provide that general perspective right from the beginning. The opening chapter gives an informal introduction to measure and integration theory. It shows that the notions of -algebra of sets and countable additivity of a set function are dictated by certain very na- ral approximation procedures from practical applications and that they are not just some abstract ideas.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 640 pp. Englisch.