Expect the unexpected: a first course in biostatistics, by Raluca Balan and Gilles Lamothe, Hackensack, New Jersey, World Scientific Publishing, 2011, xi + 242 pp., £39.99 or US$ 60.00 (hardback), ISBN 978-981-4291-32-3
This book introduces fundamental concepts and methods from Probability and Statistics and prepares the beginner for further study in the area of Biostatistics.
The book has two parts. Part I introduces the basic concepts and rules of probability theory, while Part II focuses on statistics. Probability theory has its own interest, but it also lies at the foundation of statistics. The order of the two parts reflects this logic, that is, it is important to understand the meaning of randomness before conducting any data analysis.
The topics covered in each part are carefully selected and structured into chapters. From the simplest case to the more complex, each topic is clearly explained and easily understood. For example, the concept of hypothesis testing is introduced in Chapter 11 in the form of the one sample t-test for parametric data. This concept is expanded upon to a more complex case in Chapter 12, that is, testing the relationship of two means for two independent samples and further to the more complex case of paired samples in Chapter 13.
As the book aims to introduce statistical reasoning and modelling to students in the life sciences, the authors use advanced mathematics, such as integration and differentiation, as little as possible and put an emphasis on examples. The use of examples is firstly to motivate and explain statistical and probabilistic concepts – hence giving the reader a quick understanding; secondly, to demonstrate and explore the usefulness of various statistical and probabilistic methods. For example, in Chapter 5, after introducing the definition of conditional probability through a few examples, the authors focus on the use of conditional probabilities and its derivations such as Bayes’ rule for assessing the performance of diagnostic tests with demonstration of some real life examples.
The examples used in the book are kept simple but based on real-life situations and connected to the natural sciences such as genetics, biology, ecology and health. Introducing statistical and probabilistic knowledge through such examples can easily draw students’ interest and may open a door for them to apply the knowledge in a more complex situation. Furthermore, a large number of problems are given in each chapter and also in two separate chapters. This provides sufficient examples for students to attempt and extend the knowledge they have just learned, hence leading to a deeper understanding of this subject. The reviewer also found it pleasant to read the short stories provided at the end of each chapter. Those short stories point out some key events and people in the development of modern biology.
It appears to the reviewer that the total number of errors and misprints is remarkably small indeed. In summary, this book is a good introduction to Biostatistics. It is concise, self-contained and suitable as a textbook for students of the life sciences with an interest in Biostatistics and also suitable for those people who want a quick taste of Biostatistics.