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Probability: A Graduate Course

  • Textbook
  • © 2013

Overview

  • Covers probability from a very applied perspective
  • Many exercises involve mathematical modeling of random phenomena in very practical fields, including insurance/actuarial and the life sciences/biomedicine
  • Second edition comprehensively updated, including all new exercises
  • Includes supplementary material: sn.pub/extras

Part of the book series: Springer Texts in Statistics (STS, volume 75)

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Table of contents (10 chapters)

Keywords

About this book

Like its predecessor, this book starts from the premise that, rather than being a purely mathematical discipline, probability theory is an intimate companion of statistics. The book starts with the basic tools, and goes on to cover a number of subjects in detail, including chapters on inequalities, characteristic functions and convergence. This is followed by a thorough treatment of the three main subjects in probability theory: the law of large numbers, the central limit theorem, and the law of the iterated logarithm. After a discussion of generalizations and extensions, the book concludes with an extensive chapter on martingales. The new edition is comprehensively updated, including some new material as well as around a dozen new references.

Reviews

From the reviews of the second edition:

“This book of over 600 pages gives a self-contained presentation of modern probability theory. This is an updated edition of an elementary introductory book on probability theory … . Suitable as a textbook for beginning students in mathematics, statistics, computer science or economics … . Also, it will be very useful to students and researchers in mathematics or theoretical physics.” (Teodora-Liliana Rădulescu, zbMATH, Vol. 1267, 2013)

Authors and Affiliations

  • Dept. Mathematics, Uppsala University, Uppsala, Sweden

    Allan Gut

About the author

Allan Gut is Professor of Mathematical Statistics in the Department of Mathematics at Uppsala University, Sweden. 

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