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Understanding Probability is a unique and stimulating approach to a first course in probability. The first part of the book demystifies probability and uses many wonderful probability applications from everyday life to help the reader develop a feel for probabilities. The second part, covering a wide range of topics, teaches clearly and simply the basics of probability. This fully revised third edition has been packed with even more exercises and examples and it includes new sections on Bayesian inference, Markov chain Monte-Carlo simulation, hitting probabilities in random walks and Brownian motion, and a new chapter on continuous-time Markov chains with applications. Here you will find all the material taught in an introductory probability course. The first part of the book, with its easy-going style, can be read by anybody with a reasonable background in high school mathematics. The second part of the book requires a basic course in calculus.
Table of Contents
Probability in Action
The law of large numbers and simulation
Probabilities in everyday life
Rare events and lotteries
Probability and statistics
Chance trees and Bayes' rule
Essentials of Probability
Foundations of probability theory
Conditional probability and Bayes
Basic rules for discrete random variables
Continuous random variables
Jointly distributed random variables
Multivariate normal distribution
Conditioning by random variables
Discrete-time Markov chains
Continuous-time Markov chains
Counting methods and ex
Answers to odd-numbered problems
Table of Contents provided by Publisher. All Rights Reserved.