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.
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.