Random Phenomena: Fundamentals of Probability and Statistics for Engineers, by Babatunde A. Ogunnaike, Boca Raton, CRC Taylor & Francis, 2010, xii + 1015 pp., £51.99 or US$129.95 (hardback), ISBN 978-1-4200-4497-3
‘Random phenomena’ is a hefty introduction of over a thousand pages into fundamental probability theory and statistics. As the title states, this book is clearly written from an engineering perspective and uses only a basic level of mathematics. The theory is built up from real-life examples from which the first principles are deduced. This works well as it becomes immediately clear that these principles are relevant and useful in practical situations. More examples are then used to further stress this point, deepen understanding and highlight practical problems that can be encountered in actual applications.
The book clearly explains both probabilistic and statistical concepts in minute detail and none of the essentials seem to be missing. All this is done without ever resorting to abstract mathematics, which is quite an achievement. It is hardly possible to summarise all the areas that are covered as part of this review. Suffice it to say that all the topics that one would expect to be present in an introductory course are amply covered, and that a number of more advanced topics such as hypothesis testing, regression analysis, probability model validation, nonparametric methods, reliability and life testing, quality assurance and control, multivariate analysis and experimental design are also discussed in considerable detail.
As an engineer involved in statistical data analysis, I would have loved to be taught from a book like this and I heartily recommend this book as a classroom textbook for both the clarity of the explanations and the amount of material covered. The book further accommodates such use with a large amount of review questions, exercises, application problems, and project assignments. However, the book is also suitable for self-study, to which the narrative style of the book is particularly well suited. It will allow engineers who have to deal with statistics, but lack sufficient statistical background, to easily gain fundamental insights that are readily applicable in their working environment.