[HN Gopher] Review: The Book of Why
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Review: The Book of Why
Author : pizzicato
Score : 35 points
Date : 2021-03-07 20:57 UTC (2 hours ago)
(HTM) web link (tachy.org)
(TXT) w3m dump (tachy.org)
| breck wrote:
| I like the "Ladder of causation": Rung 1:
| Associations, observational data (seeing) Rung 2:
| Intervention (doing) Rung 3: Counterfactuals (imagining)
|
| I often go in reverse order--let's figure out the cheapest clever
| ways to prove ship will sink (imagining). Then if it seems like
| it might float let's build it and throw it on the pond (doing).
| Then if it seems to float let's hop on board and see what
| happens.
| kenjackson wrote:
| I feel like I've tried to read several writings on this topic,
| mostly by Pearl. I feel like I'm good during the intro and
| motivation, but once it gets to the meat I'm completely lost. I
| feel like this is an area that would provide rich value if I
| could ever understand it.
| neatze wrote:
| Does Judea Pearl other books overlap with The Book of Why ?
| michelpp wrote:
| Yes. To me The Book of Why is sort of an approachable summary
| of his whole career culminating in his work on causal
| inference.
| michelpp wrote:
| Brady Neal has a great video course on the subject with slides
| and readings including Pearl and others:
|
| https://www.bradyneal.com/causal-inference-course
| bachmeier wrote:
| > This book dwells on the history of statistics a lot, and
| statisticians, as the authors would have you believe, are zealots
| who have conspired to keep causal thinking out of their field
| right from the start. That is, until Pearl instigated the "Causal
| Revolution", as he dubs it, the latest and greatest gift to
| modern science. I have no dog in this fight, but Pearl (whom I
| assume is the source of most of these opinions put to paper by
| Mackenzie) often comes across as wildly biased and grandiose. For
| what it's worth, I doubt that statisticians as a whole are
| anywhere as malicious or ignorant as they're portrayed in this
| book.
|
| This is correct AFAICT (I'm not a statistician even though I read
| a lot of the statistics literature). The strange thing is that
| I've never seen any obvious benefits to his comments of this
| nature. In the most generous possible reading, they are a
| distraction, with a less generous reading being that you can't
| trust his interpretation of anything.
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