Understanding Probability
Understanding Probability
$48.00
USDIn this fully revised second edition of Understanding Probability, the reader can learn about the world of probability in an informal way. The author demystifies the law of large numbers, betting systems, random walks, the bootstrap, rare events, the central limit theorem, the Bayesian approach and more. This second edition has wider coverage, more explanations and examples and exercises, and a new chapter introducing Markov chains, making it a great choice for a first probability course. But its easy-going style makes it just as valuable if you want to learn about the subject on your own, and high school algebra is really all the mathematical background you need.
- Fascinating probability problems (Monty Hall, birthday surprise, lottery winners, and more) explained in a way that anyone can understand
- Written with wit and clarity, this book offers a unique informal style to explain mathematics
- This fully revised second edition now covers all material usually taught in an introductory probability course, with many more examples and exercises in almost every chapter
Reviews & endorsements
"An excellent book for the study of basic probability events... This book is an excellent choice for advanced courses in probability for math majors who have completed the calculus sequence."
Charles Ashbacher, Journal of Recreational Mathematics
Product details
December 2007Adobe eBook Reader
9780511346262
0 pages
0kg
42 b/w illus. 22 tables 400 exercises
This ISBN is for an eBook version which is distributed on our behalf by a third party.
Table of Contents
- Preface
- Introduction
- Part I. Probability in Action:
- 1. Probability questions
- 2. The law of large numbers and simulation
- 3. Probabilities in everyday life
- 4. Rare events and lotteries
- 5. Probability and statistics
- 6. Chance trees and Bayes' rule
- Part II. Essentials of Probability:
- 7. Foundations of probability theory
- 8. Conditional probability and Bayes
- 9. Basic rules for discrete random variables
- 10. Continuous random variables
- 11. Jointly distributed random variables
- 12. Multivariate normal distribution
- 13. Conditional distributions
- 14. Generating functions
- 15. Markov chains
- Appendix
- Recommended readings
- Answers to odd-numbered problems
- Bibliography.
