I’ve read it—it’s inspired a short series I shall be posting shortly.
ETA: not a chapter-by-chapter review, though I might do that too; rather, I focus on one small aspect (the “waterline” model discussed in connection with the poker bubble) and use it to illustrate something else (tips and tricks in forecasting).
Has anyone here read the book? What did you think of it? Would you recommend it?
I’ve read it—it’s inspired a short series I shall be posting shortly.
ETA: not a chapter-by-chapter review, though I might do that too; rather, I focus on one small aspect (the “waterline” model discussed in connection with the poker bubble) and use it to illustrate something else (tips and tricks in forecasting).
I read it—I think the way I described it to the Less Wrong DC group was, “like an introductory Less Wrong article, except a book.”
To elaborate a bit:
Pro: The writing is clear and engaging.
Pro: There’s a lot of good case-study material and a bit of useful theory connecting them.
Con: The book is lacking in technical detail regarding Bayesian thinking (and his formulation of Bayes’ Theorem is kinda messy).
Con: Nate Silver is more prone to claim successful predictors as being Bayesian thinkers than he justifies in the text.
Con: There are a few glaring typos in the first printing (e.g. a table on which the “Correlated” and “Uncorrelated” column headers are switched).
It’s easy to read, and it’s worth reading for the case studies, but I’d probably put it at a “Borrow” rather than a “Buy” recommendation.
ETA: The review you posted is good.