There are many introductory textbooks on probability and statistics, for two reasons: first, there is a huge market for such books because many university courses require students to take one or more semesters of statistics; second, it is difficult to present this material well. If it were easy to strike a balance between theoretical rigor and practical application, after all, the perfect text would already have been written.
Oliver Ibe's Fundamentals of Applied Probability and Random Processes is informed by his experiences teaching the introductory probability and statistics course to junior and senior engineering students at the University of Massachusetts-Lowell, where he is a professor in the Department of Electrical and Computer Engineering. This book presents a straightforward exposition of the basics of probability and statistics, starting with basic definitions of sample space and events, and proceeding through fairly advanced topics not always included in a one-semester statistics course. Each chapter is broken down into small subunits, making this a useful reference book as well as a textbook. The material is presented clearly, and solved problems are included in the text. The text layout is particularly good, with lots of white space and logical use of headers which make it easy to locate a particular topic within a chapter. There are exercises at the end of each chapter, but no solutions provided. No reference is made to a web page or any other types of supporting materials.
Fundamentals of Applied Probability and Random Processes could be used as a probability text in many contexts, including beginning statistics classes at the graduate level. Its usefulness is not be limited to engineering departments: the examples used as illustrations are drawn from many fields. It could also serve as a self-teaching text, although the fact that apparently no solutions are available for the end-of-chapter problems makes it less useful for that purpose. However, this text assumes readers are comfortable with mathematical notation and competent in at least freshman calculus: students without good mathematical preparation (I'm thinking of many graduate student in the social sciences, for instance) may find their eyes glazing over mid-way through the second chapter.
Sarah Boslaugh, PhD, MPH, (firstname.lastname@example.org) is a Senior Statistical Data Analyst in the Department of Pediatrics at the Washington University School of Medicine in St. Louis, MO. She wrote An Intermediate Guide to SPSS Programming: Using Syntax for Data Management with Sage Publications in 2005 and is currently writing Secondary Data Sources for Public Health: A Practical Guide for Cambridge University Press. She is also Editor-in-Chief of The Encyclopedia of Epidemiology which will be published by Sage in 2007.