A First Look at Rigorous Probability Theory
eBook - PDF

A First Look at Rigorous Probability Theory

  1. 192 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

A First Look at Rigorous Probability Theory

About this book

This textbook is an introduction to probability theory using measure theory. It is designed for graduate students in a variety of fields (mathematics, statistics, economics, management, finance, computer science, and engineering) who require a working knowledge of probability theory that is mathematically precise, but without excessive technicalities. The text provides complete proofs of all the essential introductory results. Nevertheless, the treatment is focused and accessible, with the measure theory and mathematical details presented in terms of intuitive probabilistic concepts, rather than as separate, imposing subjects. The text strikes an appropriate balance, rigorously developing probability theory while avoiding unnecessary detail.

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Yes, you can access A First Look at Rigorous Probability Theory by Jeffrey S Rosenthal in PDF and/or ePUB format, as well as other popular books in Biological Sciences & Science General. We have over one million books available in our catalogue for you to explore.

Information

Publisher
WSPC
Year
2000
eBook ISBN
9789813105706
Topic
Biological Sciences
Subtopic
Science General
Index
Biological Sciences

Table of contents

  1. Contents
  2. Preface.
  3. 1. The need for measure theory. This introductory section is directed primarily to those
  4. 2. Probability triples.
  5. 3. Further probabilistic foundations.
  6. 4. Expected values.
  7. 5. Inequalities and laws of large numbers.
  8. 6. Distributions of random variables.
  9. 7. Stochastic processes and gambling games.
  10. 8. Discrete Markov chains.
  11. 9. Some further probability results.
  12. 10. Weak convergence.
  13. 11. Characteristic functions.
  14. 12. Decomposition of probability laws.
  15. 13. Conditional probability and expectation.
  16. 14. Martingales.
  17. 15. Introduction to other stochastic processes.
  18. Appendix: Mathematical Background.
  19. Bibliography.
  20. Index