Description

Book Synopsis
Instead, A Probability Path is designed for those requiring a deep understanding of advanced probability for their research in statistics, applied probability, biology, operations research, mathematical finance and engineering.

Trade Review

From the reviews:

“This introduction to measure-theoretic probability is intended for students whose primary interest is not mathematics but statistics, engineering, biology, or finance. The book is a welcome reprint in paperback … . The book’s pace … is ‘quick and disciplined’.” (William J. Satzer, MAA Reviews, March, 2014)



Table of Contents
1 Sets and Events.- 2 Probability Spaces.- 3 Random Variables, Elements and Measurable Maps.- 4 Independence.- 5 Integration and Expectation.- 6 Convergence Concepts.- 7 Laws of Large Numbers and Sums of Independent Random Variables.- 8 Convergence in Distribution.- 9 Characteristic Functions and the Central Limit Theorem.- 10 Martingales.- Index.- References.

A Probability Path Modern Birkhuser Classics

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    A Paperback by Sidney I. Resnick

    15 in stock

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      Publisher: Birkhauser Boston
      Publication Date: 11/14/2013 12:00:00 AM
      ISBN13: 9780817684082, 978-0817684082
      ISBN10: 0817684085
      Also in:
      Mathematics Applied mathematics Probability and statistics Stochastics

      Description

      Book Synopsis
      Instead, A Probability Path is designed for those requiring a deep understanding of advanced probability for their research in statistics, applied probability, biology, operations research, mathematical finance and engineering.

      Trade Review

      From the reviews:

      “This introduction to measure-theoretic probability is intended for students whose primary interest is not mathematics but statistics, engineering, biology, or finance. The book is a welcome reprint in paperback … . The book’s pace … is ‘quick and disciplined’.” (William J. Satzer, MAA Reviews, March, 2014)



      Table of Contents
      1 Sets and Events.- 2 Probability Spaces.- 3 Random Variables, Elements and Measurable Maps.- 4 Independence.- 5 Integration and Expectation.- 6 Convergence Concepts.- 7 Laws of Large Numbers and Sums of Independent Random Variables.- 8 Convergence in Distribution.- 9 Characteristic Functions and the Central Limit Theorem.- 10 Martingales.- Index.- References.

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