Probability - Modular Mathematics Series

Probability is relevant to so many different subject areas that its importance as a mathematical technique cannot be underestimated. This book provides a comprehensive, user-friendly introduction to the subject. The step-by-step approach taken by the author allows students to develop knowledge at their own pace and, by working through the numerous exercises, they are ensured a full understanding of the material before moving on to more advanced sections. Traditional examples of probablistic theory, such as coins and dice, are included but the author has also used many exercises based on real-life problems. The result is an introduction to probability that avoids the overly confusing, theoretical approach often adopted in this area, and provides a simple and concise text that will be invaluable to all studying first and second year courses on the subject.

Modelling uncertainty * Sample space and events * Definitions of probability * Equally-likely outcomes * The axioms of probability * Conditional probability and independence * Bayes' theorem * Discrete random variables * The binomial and related distributions * Other special discrete distributions * Moments * Continuous random variables * The normal distribution * Functions of a random variable * Bivariate discrete distributions * Sums of independent random variables * The Central Limit theorem * Final thoughts * Answers to selected exercises * References * Index * Appendix 1 - Table of random digits * Appendix 2 - Table of the standard normal cumulative distribution function * Index.