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Sarah Boslaugh holds a PhD in Research and Evaluation from the City University of New York and have been working as a statistical analyst for 15 years, in a variety of professional settings, including the New York City Board of Education, the Institutional Research Office of the City University of New York, Montefiore Medical Center, the Virginia Department of Social Services, Magellan Health Services, Washington University School of Medicine, and BJC HealthCare. She has taught statistics in several different contexts and currently teaches Intermediate Statistics at Washington University Medical School. She has published two previous books: An Intermediate Guide to SPSS Programming: Using Syntax for Data Management (SAGE Publications, 2004) and Secondary Data Sources for Public Health (forthcoming from Cambridge U. Press, 2007) and am currently editing the Encyclopedia of Epidemiology for SAGE Publications (forthcoming, 2007).
Paul A. Watters PhD CITP, is Associate Professor in the School of Information and Mathematical Sciences and Centre for Informatics and Applied Optimization (CIAO) at the University of Ballarat. Until recently, he was Head of Data Services at the Medical Research Council's National Survey of Health and Development, which is the oldest of the British birth cohort studies, and an honorary senior research fellow at University College London. He uses multivariate statistics to develop orthogonal and non-orthogonal methods for feature extraction in pattern recognition, especially in biometric applications.
On the one hand I like the book because of its scope and the overall presentation. What I find disturbing is the high amount of errors in all kinds of content (typos, formular errors, table errors, false figures, and so on). Also not great is that the solutions to the problems are given right after the problem itself so it is really hard not to look at the solution before starting to work on the problem. Somebody corrects all those errors and this is a great book on statistics. Right now the errata page at the publisher's web site is just too long.
This book is a reasonably well written introduction to a variety of useful statistical concepts. It is far more readable than the average stats textbook. However, there clearly was some sort of failure in the copy editing process. This book is riddled with small, niggling errors which taken individually aren't so bad, but as a group are very annoying. These errors are not just typos; figures are mislabeled and referenced, the worked through examples contain mathematical errors (including miscalculation of means, etc.), and at least one formula is simply incorrect! These annoying quirks keep this book from being the clear concise text it could be, and no book can be a "Quick Reference" if you can't be sure that what you are looking up is correct! That said, if you take the time as a reader to work through the examples and make sure that the each formula makes mathematical sense, you can get something out of this book.
I recently received this book and immediately went to the O'Reilly errata [...]There was an extensive list, but after going through it I found that about 80% of the errors noted on it had already been corrected despite the fact that the book I received is still marked "First Edition".
I have yet to read the book, so please take my 4 star rating with a grain of salt, but I had to include that to publish this review. That being said, the fear of excessive typos and errors should no longer deter you from considering this book.
This book is probably not what you're expecting since most O'Reilly Nutshell books assume you already have thorough knowledge of a subject and you are just looking for "cues" in case you forget something. This book is more of a "Head First" type of book in that it assumes no prior knowledge of the subject. Since O'Reilly is planning a Head First book on Statistics, I'd like to see the difference between this book and that one.
This book focuses on using and understanding statistics in a research or applications context, not as a discrete set of mathematical techniques but as part of the process of reasoning with numbers. It integrates the discussion of issues such as measurement and data management into an introductory statistics text. It serves as an introductory statistics book that is compact, inexpensive, and easy for beginners to understand without being condescending or overly simplistic.
The audience for this book includes students taking introductory statistics classes in high schools, colleges, and universities, professionals who need to learn statistics as part of their current jobs, and finally people who are interested in learning about statistics out of intellectual curiosity.
The book focuses on statistical reasoning. In particular, the book focuses on thinking about data, and using statistics to aid in that process.
The book is organized into four parts: introductory material (Chapters 1-6) that lays the necessary foundation for the chapters that follow; elementary inferential statistical techniques (Chapters 7-11); more advanced techniques (Chapters 12-16); and specialized techniques (Chapters 17-19).Read more ›
I purchased this book to brush up on some of the more advanced topics in statistics. As I remembered my undergrad stats experience to be a lot of proofs, I was drawn in by the "solid understanding without the numbing complexity of most textbooks" on the back cover.
There are just too many errors to be useful. I found myself going back more and more to my old statistics textbook from college. The examples are clearer and there are better problems to work through. And guess what? You can skip over the "numbing complexity" and still get more from a textbook than you will from "Statistics in a Nutshell."
Furthermore, I don't trust this title as a reference, as I typically have to validate what I'm researching with another textbook. It's quicker and easier to go to a source you know is correct from the start.
O'Reilly really needs to step up for this sloppy book: correct the mistakes and offer those of us with the first versions a free trade-in to the corrected version.
I have read many popular statistics books and textbooks. This is quite possibly the best-written book of it's type, a concise introduction/review, and introductory (first-year stats) reference. I'm writing this because I don't think the existing reviews generally give this book enough credit. What's so good about it?
(1) The writing: very clear and concise. But not so concise so as to be difficult or "mysterious." When reading the book, there there several times when I read something, didn't quite understand the point, was certain that the author had too quickly skimmed over the topic, only to turn the page and see a clear two or three paragraph explanation of the point I was trying to understand. The level at which the material is covered is just perfect for this sort of use: not too short so as to leave something out; not too long so as to make topics too complicated. The questions at the end of chapters are "just right" too. They are well chosen, clear, not superficial, but not too difficult.
(2) The organization of topics is very well done. The flow is very natural, and lends itself to effective and efficient coverage of the material.
This may not be the best book to learn statistics from scratch (perhaps a bit too concise, but actually still not too bad), and certainly not a good choice if you are looking for coverage or a reference for advanced topics. But if you are looking for a review, and perhaps an easy to read basic statistics reference, it can't be beat. Quite possibly the best book for this purpose available.