Comment by geokon

Maybe my expectations were too high given all the online praise, but I've been working through it for the past two weeks and I've been underwhelmed:

- The language is often very vague and imprecise, so it's more difficult than it feels it should be

- Concepts are sometimes introduced "at random" in ways that only really make sense in hindsight. So as you're reading you're left scratching your head as to why something was brought up.

- There are constant philosophical and historical digressions that seem to hold deeper meaning, but maybe once you know the topic already.

- Similarly, constantly talking about people that take issue with the method. People not liking the method is a constant theme (they seem really butthurt about this?). But the craziest part is this all done before you even really understand what the method is!!

- The editor must have placed some strict requirement of saying "Bayesian" at least five times per page.

- No index. Useless table of context. But lots of end-notes you feel compelled to flip to constantly

Overall it feels like a textbook written to impress other statistics professors - and as an outlet for the author to air some frustrations with how people do statistics (which may be completely valid!)

The overall structure and objectives seem solid for the most part. It's just a lot of the details aren't great. The problems (so far) have been good. The examples in the text are fun and compelling, but you have to do your own legwork to actually pick through all the prose and tie the pieces together - to figure how it fits together mathematically. Fortunately AI helps as a tutor