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3044 results in Probability theory and stochastic processes

Page 68 of 153

The Surprising Mathematics of Longest Increasing Subsequences
  • Dan Romik
  • Published online:
    05 October 2014
    Print publication:
    02 February 2015
  • In a surprising sequence of developments, the longest increasing subsequence problem, originally mentioned as merely a curious example in a 1961 paper, has proven to have deep connections to many seemingly unrelated branches of mathematics, such as random permutations, random matrices, Young tableaux, and the corner growth model. The detailed and playful study of these connections makes this book suitable as a starting point for a wider exploration of elegant mathematical ideas that are of interest to every mathematician and to many computer scientists, physicists and statisticians. The specific topics covered are the Vershik-Kerov–Logan-Shepp limit shape theorem, the Baik–Deift–Johansson theorem, the Tracy–Widom distribution, and the corner growth process. This exciting body of work, encompassing important advances in probability and combinatorics over the last forty years, is made accessible to a general graduate-level audience for the first time in a highly polished presentation.

Probability and Statistics by Example
  • Volume 1, Basic Probability and Statistics, 2nd edition
  • Yuri Suhov, Mark Kelbert
  • Published online:
    05 October 2014
    Print publication:
    22 September 2014
  • Probability and statistics are as much about intuition and problem solving as they are about theorem proving. Consequently, students can find it very difficult to make a successful transition from lectures to examinations to practice because the problems involved can vary so much in nature. Since the subject is critical in so many applications from insurance to telecommunications to bioinformatics, the authors have collected more than 200 worked examples and examination questions with complete solutions to help students develop a deep understanding of the subject rather than a superficial knowledge of sophisticated theories. With amusing stories and historical asides sprinkled throughout, this enjoyable book will leave students better equipped to solve problems in practice and under exam conditions.

The Doctrine of Chances
  • Or, a Method of Calculating the Probability of Events in Play
  • Abraham de Moivre
  • Published online:
    05 October 2014
    Print publication:
    27 June 2013
    First published in:
    1738
  • A Huguenot exile in England, the French mathematician Abraham de Moivre (1667–1754) formed friendships with such luminaries as Edmond Halley and Isaac Newton. Making his living from private tuition, he became a fellow of the Royal Society in 1697 and published papers on a range of topics. Probability theory had been pioneered by Pascal, Fermat and Huygens, with further development by the Bernoullis. Originally published in 1718, The Doctrine of Chances was the first English textbook on the new science and so influential that for a time the whole subject was known by the title of the work. Reissued here is the revised and expanded 1738 second edition which contains the remarkable discovery that when a coin is tossed many times, the binomial distribution may be approximated by the normal distribution. This version of the central limit theorem stands as one of de Moivre's most significant contributions to mathematics.

  • Preface

  • Yuri Suhov, University of Cambridge, Mark Kelbert, Swansea University
  • Book:
    Probability and Statistics by Example
    Published online:
    05 October 2014
    Print publication:
    22 September 2014, pp vii-xiv

  • Summary

    The original motivation for writing this book was rather personal. The first author, in the course of his teaching career in the Department of Pure Mathematics and Mathematical Statistics (DPMMS), University of Cambridge, and St John's College, Cambridge, had many painful experiences when good (or even brilliant) students, who were interested in the subject of mathematics and its applications and who performed well during their first academic year, stumbled or nearly failed in the exams. This led to great frustration, which was very hard to overcome in subsequent undergraduate years. A conscientious tutor is always sympathetic to such misfortunes, but even pointing out a student's obvious weaknesses (if any) does not always help. For the second author, such experiences were as a parent of a Cambridge University student rather than as a teacher.

    We therefore felt that a monograph focusing on Cambridge University mathematics examination questions would be beneficial for a number of students. Given our own research and teaching backgrounds, it was natural for us to select probability and statistics as the overall topic. The obvious starting point was the first-year course in probability and the second-year course in statistics. In order to cover other courses, several further volumes will be needed; for better or worse, we have decided to embark on such a project.

Page 68 of 153