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.
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.
First and second year mathematics undergraduates and those taking a mathematics option as part of a science or engineering course.
- No. of pages:
- © Butterworth-Heinemann 1995
- 17th May 1995
- Paperback ISBN:
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"This book is well produced ... I can strongly recommend this as a source book for lecturers and teachers" Teaching Statistics
Department of Statistics, University of Glasgow, UK