Uri Bram writes popular books with a conceptual, visual approach to statistics. Bram believes that it is possible to learn statistical concepts without understanding statistical techniques, and that the concepts on their own can be a huge help for students when examining and interpreting the world around us. Contact Uri at uri uribram. Check out his homepage.

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Shelves: statistics , reading-for-knowledge The book was well worth the read for a beginner. It took me around 1 hour and 20 minutes to read the whole thing, and came out with around a dozen insights. It was mostly a book teaching you how to think statistically no way!

It covers selection bias, base line fallacy, a bit of Bayesian statistics, some logical The book was well worth the read for a beginner. It covers selection bias, base line fallacy, a bit of Bayesian statistics, some logical fallacies, and a bunch of other things. A good way to spend 80 minutes. It fills the gap between simple one page introductions to stats and the complexity of an introductory statistics course.

I am primarily interested in making Bayes a more central part of my thought process, and help from books like this moves me in that direction. My primary criticism is that I think the author switches levels rather abruptly. After using language and explanations that would draw in even a non-mathematical thinker, he introduces equations that might be confusing for those rusty on their algebra or algebraic notation.

None of these are particularly gnarly equations. However, a notation like: P Hypothesis Evidence which someone familiar with the notation would read as "the probability of the hypothesis given the evidence" would not be accessible of one was not familiar with P or with. Please understand that this is not a major problem, and that anybody who has taken or is taking a stats course will have no difficulty with the notation. The only reason I make this point is that with some effort to simplify the mathematical notation, the rest of the book would make these concepts available to an even broader range of readers.

For me working in this field the benefit was in getting a few nice examples to use when explaining some of these concepts, rather then learning anything new. One Very nice!

One failing: some examples were nice, but some were awful boy who hits people after sneezing? Also graphical examples could have been leveraged far more, Bram kept it at the most rudimentary. If this was a paper book, the publisher would be compelled to pad this to pages with fluff. As it is it now, it is short, interesting and educational.


Thinking Statistically



Review: 'Thinking Statistically' by Uri Bram


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