Book review of Statistics in a Nutshell 2nd ed. by Sarah Boslaugh

Statistics in a Nutshell by Sarah Boslaugh
My rating: 4 of 5 stars

One of the biggest problems faced in teaching statistics is the gap between learning the methods to actually using them. Statistics classes that are based on learning formulas fail due to the disconnect between learning formulas and the reality that very rarely are these methods used by implementing the formulas that are so painstakingly taught. But learning statistics as a set of steps or functions in a computer package only gets a little further. The real goal should be what methods should be used and why. The how is almost secondary. Statistics in a Nutshell focuses on the what and the why. I would not use this to learn how to perform a technique or its formulas, but this is where to go to understanding how the various methods of statistical analysis should be used and their qualities. It is meant to be read, not just studied, and as such it holds a different place than other statistics texts.

When I first learned statistics, the focus was on learning formulas that calculated various values. But the problems I could work on were only toys, and it took so long that we did not get into much of understanding what we were dong. Now with readily available software packages, the temptation is to focus on the mechanics of implementing a procedure on a set of data and reading the computer output. But software documentation and even books that teach statistics fall into the trap of focusing on how a method works then applying it and not as much on why. Part of this is because of the pressure of having to cover topics, but the fact that the methods are presented in isolation, without their application context so it is rare to grapple with the question of how to know what needs to be done and instead the focus is on how to do it.

Statistics in a Nutshell is the other kind of book. I was taught that for computer programming for any language you wanted a book that focused on methods, but also a book that focused on morals, the why you use a language feature. This is the morals book for statistical programming. You read it, not to learn how to calculate statistical output or implement visualizations, but to think about what method or visualization is appropriate to help understand the data and environment and to communicate those truths to an audience.

Because of the expectation that any course that teaches statistics gives the students a toolkit, this would never be a good book for teaching a course. But in the real world, what is more important is that you understand what these statistical methods are and why you use one over the other. So for the data analyst or a student who needs an overview of everything this is ideal. It would also be ideal for someone who may not have the time to go into detailed study of statistical methods, but needs to interpret the results or work with statisticians and data analysts. This book will help interpret what you get and ask the right questions to both understand statistical results and perhaps point those who are doing the analysis in the right direction so that they are answering the right questions.

Note: I received a free electronic copy of Statistics in a Nutshell through the O'Reilly Press Bloggers program.

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