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A Basic Course in Measure and Probability: Theory for Applications

A Basic Course in Measure and Probability: Theory for Applications

A Basic Course in Measure and Probability: Theory for Applications Hardback - 2014

by Ross Leadbetter

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Hardcover. New. New Book; Fast Shipping from UK; Not signed; Not First Edition; This concise introduction covers all of the measure theory and probability most useful for statisticians. Originating from the authors' own graduate course, it is perfect for a two-term course or for self-study. It is especially useful
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Details

  • Title A Basic Course in Measure and Probability: Theory for Applications
  • Author Ross Leadbetter
  • Binding Hardback
  • Condition New
  • Pages 376
  • Volumes 1
  • Language ENG
  • Publisher Cambridge University Press
  • Publication date 2014-01-30
  • Bookseller's Inventory # ria9781107020405_inp
  • ISBN 9781107020405 / 1107020409
  • Weight 1.5 lbs (0.68 kg)
  • Dimensions 9.1 x 6.1 x 0.9 in (23.11 x 15.49 x 2.29 cm)
  • Themes
    • Aspects (Academic): Science/Technology Aspects
  • Category Mathematics
  • Library of Congress subjects Probabilities, Measure theory
  • Library of Congress Catalogue Number 2013028841
  • Dewey Decimal Code 515.42
  • Quantity available 462

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Reader reviews for A Basic Course in Measure and Probability: Theory for Applications

From the publisher

Originating from the authors' own graduate course at the University of North Carolina, this material has been thoroughly tried and tested over many years, making the book perfect for a two-term course or for self-study. It provides a concise introduction that covers all of the measure theory and probability most useful for statisticians, including Lebesgue integration, limit theorems in probability, martingales, and some theory of stochastic processes. Readers can test their understanding of the material through the 300 exercises provided. The book is especially useful for graduate students in statistics and related fields of application (biostatistics, econometrics, finance, meteorology, machine learning, and so on) who want to shore up their mathematical foundation. The authors establish common ground for students of varied interests which will serve as a firm 'take-off point' for them as they specialize in areas that exploit mathematical machinery.
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