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on January 22, 2012
This book offers a simple, engaging introduction to key statistical concepts. More advanced students may not encounter any new concepts* but they will be helped by the author's intuitive explanations that make the fundamentals taught in years of statistics and social science courses make sense like never before.

I highly recommended this book, especially for: beginning students looking to get some initial motivation to study statistics or a short, fun intro to key concepts (or eager parents who want to encourage interest in statistics); intermediate/advanced students who want to get more excited by the subject matter or are looking for intuitive explanations of the concepts covered in the book (selection bias, endogeneity, Bayes Theorem); and anyone who wants to seem smart at dinner parties.

*They will learn why they likely won't save money by switching to Geico.
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on November 9, 2011
Perversely, the best compliment I can give this book is to warn prospective readers against relying on it's very high reviews, because of the inherent selection bias in the sample of reviewers relative to the entire population of readers.

Seriously, though, it was a truly excellent read and far more fun than a book about statistics has any right to be. So just this once, ignore the selection bias and trust the 5 stars.
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on October 30, 2011
Really well done, particularly the section on perception and selection bias (especially enjoyed examples on why it seems like we forget people's names way more than they forget ours, and interpreting a skewed sample of comments after an open mic night). Great introduction to Bayesian thinking as well. Rigorous in being correct mathematically, but no barriers to entry there for people new to the concept, either.

In short: I enjoyed your performance! Quit your day job!
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on January 20, 2013
Good for people who are intimidated by numbers and equations, but still wnat ot know some of the tricks commonly used to decieve the public by the media, government agencies, and corporate world. Learn why "switching" data always makes the advertiser look better than they are, how census numbers are used to lie to you, etc.
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on January 31, 2016
Great introduction to statistics; good read for those easily intimidated by equations; fun and practical examples -- all of these, as other reviewers have highlighted are true. That said, personal experience shows (insert selection bias warning here) that all of us, including those who studied statistics, are comfortable with equations, and may even need to apply these techniques in our professions... still manage to forget, stumble, and mess up the basics. And the best recourse is to periodically remind yourself of the basics - e.g. read a book like this one.

Why do the Geico ads make no sense? Is your boss really as ignorant as you think, or is there something else at work? Is your girlfriend cheating on you?

Read this book (it's a quick one) to figure out how to approach these (and other) questions with some statistical rigor. It's a fun read.
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on December 11, 2012
The introduction to Bayesian thinking is quite nice. I have used Bram's style and examples to explain the concepts to new students with great success. A very valuable book for anyone who needs to kick start statistical thinking in students.
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on December 26, 2012
A quick and concise explanation of three common errors made when evaluating statistical information. Often used by politions and the media to confuse (themselves as well).

May need a couple of reads to sink in.
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First of all, I was disappointed. I hate it when I order one of these short books. But that is my fault, so no one to blame. I am an engineer, and use statistics all the time, so there was nothing new in the book for me. But I often struggle with explaining statistics to non-technical colleagues, and am always on the lookout for good ways to do that.

=== The Good Stuff ===

*Bram's section on selection and sampling biases is dead-on. He uses simple examples and drives home his points. In my applications, this is one of the more important areas for training. We never let junior manufacturing technicians do complex statistical analysis, but we often give them tremendous latitude in sampling plans.

=== The Not-So-Good Stuff ===

* The author loses his touch when it comes to the Bayesian theorem. He gets the statistics correct, but the explanation is very wordy and plagued by several convoluted sentences. Further, in his desire to make sure there is "no math", he turns what could be a relatively simple set of equations into paragraphs of text. I understand the concepts, but had to read it several times to make sure I understood where he was going.

=== Summary ===

Those are really the only two topics covered in the short book. If you are buying it to learn statistics, or as a study aid, I'd suggest looking elsewhere. Perhaps the most useful section of the book is where the author describes how a 99% effective medical test for a relatively rare disease is roughly as useful as flipping a coin. It should be a required reprint in every Doctor's office.
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on January 17, 2016
Cool reading. Not much for the "stats part" but for the author style. The book gives you the sense of looking for error in statements and what we consider "facts". Not everything seems to be as it looks like. Good buy.
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on November 11, 2012
The problem with numbers is that they can't be easily described...unless, the teacher can cite specific examples that illustrate the concepts being taught. However, to understand the example given, one must have, at least, a basic understanding of the subject, in this case, numbers and statistics. Though this book begins with a noble mission to help the "normal" person understand statistics, it quickly gets bogged down in the known versus the understandable; unfortunately, the reader, at least, this reader, was just a lost at the end of the book as he was at the beginning.
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