Customer Reviews

The Statistical Sleuth: A Course in Methods of Data Analysis

5 star:		(10)
4 star:		(2)
3 star:		(2)
2 star:		(2)
1 star:		(4)

 

 

I have taught using this text 5 times now. I like the concept very much. My goals are to teach the students how to choose appropriate statistical tests and how to write up their results professionally. I very much like the concept of "project" exercises with real data sets.

Unfortunately, many of the datasets contain faulty data. I doubt that I have a full list of example, but Chapter 2, Problem 23 supposedly contains percent change in fatalities in states that retained and did not retain 55 mile per hour speed limits between 1995 and 1996. Unfortunately, the data reported have nothing in common with the real data. For instance, there were 87 fatalities in Alaska in 1995 and 81 in 1996 leading to a 7% decrease. The number used in the text is a 29% decrease. Other examples include Chapter 8, Problem 20 which is admittedly an approximation but the authors did not read the scale on the New York Times graphic correctly which places the supposed outlier rather differently than if the correct scale for the data is used. In Chapter 11, problem 24, there is an excessively heavy grasshopper mouse among other errant species weights.

The concept is great, a few data entry errors can be an effective learning tool, but too many blatantly incorrect datasets that lead to conclusions diametrically opposed to the real data seems sloppy to me.

This is a superb text for graduate students or advanced undergraduates. The case studies are excellent, and the approach is innovative. The strength of the book is its coverage of regression models (linear algebra not used - a weakness if you want to program in Matlab, but ok for SPSS). The examples are drawn from Ecology (esp. Island biogeography), Evolutionary biology, geochemistry, environmental policy, medicine and law. There is something of interest for even the most diverse audience.

During my professional life I was several times in the situation of having to do statistical analysis of some data. I also saw other colleagues struggle with the same situation and it seems that for someone without a formal training in statistics and a lot of practical experience this is a strange mixture of technical know-how, guess-work and pure superstition.

This is the book I've been looking for for years now, to learn how to do the job with a reasonable understanding of the choices involved and the assumptions that are made when using this or that tool. It is a wonderfully practical and clear exposition of the methods that are likely to be used by a practitioner to answer practical questions with the help of data - and definitely helps to avoid the uneasy feeling of having to apply some tool without really knowing what is going on.

This unique book has it's good points. It attmepts to show how to use different types of statistical analyses work together and what order to use them in.

However, it is poorly written. The authors will start to use terms and ideas that may or may not be defined two or ten pages later, or maybe in a following chapter and you're never quite sure if something will be explained or whether this is something you should already know. This makes for a slow and aggrevating read to the neophyte. Sometimes it seems like a concise statement of the subjects it addresses, but maybe only after you already have mastered them.

If the authors reread the book with a fresh eye, it could be edited and rewritten into a real treasure. Excellent start

I have read more than 100 statistical texts on various subjects. This book is one of the best I've ever seen. It is extremely clear, well-organized, consistent in methodology and well-typeset. The use of well-documented case studies to illustrate every concept makes eclectic reading easy. The book also attempts to answer common trade-offs and philosophical points clearly. If I were teaching statistics, I'd use this text somewhere at the junior year level. I'd highly recommend it as a quick reference to anyone working with and familiar with statistics. It's very useful for a quick conceptual and practical overview.

This book is a great guide for those who have already had a few courses on statistics. What this book does for you is helps you figure out which tool is the right tool for the job.

This solution's manual is a RIP-OFF!!!
It's only a "Student" solutions manual, so most of the problems in the book are missing.
Also, all the solutions are already available for free at www dot statisticalsleuth dot com
Don't buy this book. I returned mine as soon as I figured all this out

This is a great introductory statistics book, for students who are taking beginning level stats courses. The examples are cleary laid out and it's not too heavy on the theory.

In a very clear way the author explains all the concepts you need to know about data analysis, and also uses some graphs and figures to better describe the use of formulas, or to understand the outcome from the exercises. The book has many examples from real life that allows the student to better understand the concepts and how do they apply in real life, making the learning process more enjoyable.

This textbook has been helpful for my graduate-level statistics course. While the lecturer does not use the text explicitly for lecture or homework, it has been helpful in further understanding the course material.