Probability and Measure

Probability and Measure

4.25 (43 ratings by Goodreads)
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Borel's normal number theorem, proved by calculus alone, followed by short sections that establish the existence and fundamental properties of probability measures, presenting lebesque measure on the unit interval. Coverage includes key topics in measure, integration, random variables and expected values, convergence of distributions, derivatives and conditional probability and stochastic processes.
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Product details

  • Hardback | 636 pages
  • 162.56 x 231.14 x 35.56mm | 1,065.94g
  • John Wiley & Sons Inc
  • New York, United States
  • English
  • Revised
  • 2nd Revised edition
  • illustrations, bibliography, index
  • 0471804789
  • 9780471804789

Table of contents

Probability; Measure; Integration; Random Variables and Expected Values; Convergence of Distributions; Derivatives and Conditional Probability; Stochastic Processes; Appendix; Notes of the Problems; Bibliography; List of Symbols; Index.
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Rating details

43 ratings
4.25 out of 5 stars
5 44% (19)
4 42% (18)
3 9% (4)
2 5% (2)
1 0% (0)
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