Principles of Biostatistics Description:

Principles of Biostatistics review:
1 stars (the "never again" book for biostatistics) - Let me just start by saying I really like math, but this book did not help me to learn biostatistics at all. It doesn't explain the issues and equations very well and it has absolutly no answers in the back to check with yours, that's a whole other book...and that only has answers to the odds. Perhaps this would be a decent book for anyone who already has a handle on the subject and wants to learn more, but if this is your first exposure to biostatistics, like me, try another source to learn from, this book makes a difficult subject near impossible.
2 stars (Social scientists beware - research other options) - I'm a postdoctoral level biomedical researcher who has used many other biostatistics books before. This book is currently used for entry-level biostatistics at my School of Public Health. The bonus is that this book is geared towards epidemiology (eg, there is a chapter on rates and standardization), and I liked the CDROM that comes with the book and contains datasets.



Unfortunately, the authors have chosen to derive many key concepts from probability theory. This is fine if you are comfortable with probability concepts. However, most students with background in social sciences are not: thus I found that this approach often adds an unnecessary level of complexity.



Most of the examples are long-winded, dragging on from page to page - flipping back and forth is extremely frustrating, and the layout makes it difficult to grasp what the point of each example is. Also, the long-winded style makes this book a poor desk reference if you just quickly need to check a formula or definition. Sadly I have to say that I very rarely use this $100 book - there are plenty of more accessible and succinct entry-level texts that cost a fraction of this volume. And yes, Google is better learning tool than this book.
2 stars (Muddled presentation of concepts) - Principles of Biostatistics certainly presents all of the information that one needs to know in order to succeed in Biostatistics. Yet, the concepts are presented in a manner less logical than they deserve.



Key concepts and definitions need to be clearly marked, if only with bold text. Examples of problems are frequently overly verbose and lose me when I'm trying to understand what's going on.



I think that the fundamentals of a good textbook are here, but it needs a thorough reversioning with content and typographic editing before it can be considered a winner.



My overall experience with the book is not great.