Need to learn statistics as part of your job, or want some help passing a statistics course? Statistics in a Nutshell is a clear and concise introduction and reference that's perfect for anyone with no previous background in the subject. This book gives you a solid understanding of statistics without being too simple, yet without the numbing complexity of most college texts. You get a firm grasp of the fundamentals and a hands-on understanding of how to apply them before moving on to the more advanced material that follows. Each chapter presents you with easy-to-follow descriptions illustrated by graphics, formulas, and plenty of solved examples. Before you know it, you'll learn to apply statistical reasoning and statistical techniques, from basic concepts of probability and hypothesis testing to multivariate analysis. Organized into four distinct sections, Statistics in a Nutshell offers you:

• Introductory material:

• Different ways to think about statistics

• Basic concepts of measurement and probability theory

• Data management for statistical analysis

• Research design and experimental design

• How to critique statistics presented by others

• Basic inferential statistics:

• Basic concepts of inferential statistics

• The concept of correlation, when it is and is not an appropriate measure of association

• Dichotomous and categorical data

• The distinction between parametric and nonparametric statistics

• Advanced inferential techniques:

• The General Linear Model

• Analysis of Variance (ANOVA) and MANOVA

• Multiple linear regression

• Specialized techniques:

• Business and quality improvement statistics

• Medical and public health statistics

• Educational and psychological statistics

Unlike many introductory books on the subject, Statistics in a Nutshell doesn't omit important material in an effort to dumb it down. And this book is far more practical than most college texts, which tend to over-emphasize calculation without teaching you when and how to apply different statistical tests. With Statistics in a Nutshell, you learn how to perform most common statistical analyses, and understand statistical techniques presented in research articles. If you need to know how to use a wide range of statistical techniques without getting in over your head, this is the book you want.

Amazon.com® Reader Reviews (Ranked by Helpfulness)

Average Amazon.com® Rating:  Based on 14 Ratings

Wait for the second edition. - 2009-03-03
Reviewer Rating:
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.

Most Errors Have Been Corrected. - 2009-06-19
Reviewer Rating:
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.

Too many errors. - 2009-05-10
Reviewer Rating:
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.

Good for a middle school statistics class - 2009-04-27
Reviewer Rating:
The book was cute, but not for anyone who has passed algebra. I was disappointed because the book was recommended by an engineering trade journal. It is a good book for my kids though. If you do not have a technical career (perhaps business), this is a good book for you.

Excellent road map to selecting a statistical test - 2009-05-27
Reviewer Rating:
For a very long time I had been looking for a basic book--a sort of map if you will--to the myriad number of statistical tests available for conducting research. After speaking to multiple people and reviewing many books, I finally stumbled into two gems. The first one is Learning to use statistical tests in psychology by Judith Greene and Manuela D'Oliveira (209 pp.) Learning to Use Statistical Tests in Psychology. I loved the second edition but bought the third edition, which follows a similar line. In the third edition, however, the most important feature of the book, a set of decision charts fell off. The third edition only includes one chart and so you better make sure it is included before you buy, or write to Open University Press and they will send you a PDF you can print and paste in the back cover. The book is interesting and reads like a page turning novel. The focus is on helping you decide which of the many statistical tests should be selected when conducting a research study. I was looking for a book that spoke about Likert-type questions and the analysis required (answer = Chi-square) and was surprised that Likert scales are not mentioned. The advantage of the Greene-D'Oliveira book is that it has the decision chart and is translated into Spanish (which is important for me). A week later I found the second book, Statistics in a Nutshell: A Desktop Quick Reference by Sarah Boslaugh and Paul Andrew Watters (O'Reilly, 452 pp.) that had everything I was looking for and more. The book is also very well written and entertaining. It has a better index and includes a discussion of Likert scales and the Chi-square. Besides being more thorough, Boslaugh-Watters provide a better discussion of statistical packages. If I could only choose one of the two books, I would purchase Boslaugh-Watters, but I am thrilled to have found both of these superb reference books.

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