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How does it compare/contrast with: - Wasserman's All of Statistics? (which I haven't read/worked on) - Downey's Think Stats and Think Bayes? (which I've read
by fizixer 9y ago
How does it compare/contrast with:
- Wasserman's All of Statistics? (which I haven't read/worked on)
- Downey's Think Stats and Think Bayes? (which I've read in bits and pieces and have found amazing)
- Any other well known Stats or Probability text?
- pencilcode 9y agoAlthough old, I really like Principles of Statistics by Bulmer. Duke’s MOOC is pretty good btw.
- lukego 9y agoI'm a non-mathematician stats newbie but here is my take: Strength of this book seems to be that it is very approachable in a "plain english" kind of a way. This is the first time I have seen it and I'm looking forward to reading it. Strength of _All of Statistics_ is that it is fast-paced and approachable even though it is essentially a math textbook. You only need a bit of algebra to make sense of it. That book exudes the feeling that the author wants to get through all this theory as quickly as possible to move onto other exciting things. (_All of Nonparametric Statistics_ by the same author is actually less approachable and shouldn't be taken as a simplified "the good bits" subset.) The stats book that I have had the most value out of is _Statistical Modeling: A Fresh Approach_. It's fundamentally about making sense of different kinds of data using a computer. http://www.mosaic-web.org/go/StatisticalModeling/ http://www.mosaic-web.org/go/StatisticalModeling/
- random_moonwalk 9y agoRegarding All of Statistics, the author states that the 'reader is assumed to know calculus and a little linear algebra'. It's a good book, though think you'd have a tough time with only 'a bit of algebra'.