, 5 tweets, 2 min read Read on Twitter
1/5r
No offense, and I appeciate your sharing impressions with other readers. I am even more grateful for mentioning @StatModeling which should give readers a glimpse at how some 2019 statisticians think. I quote: "I find it baffling that Pearl and his colleagues keep taking
2/5
statistical problems and, to my mind, complicating them by wrapping them in a causal structure." This quote from Gelman's blog should enter the archives of scientific revolutions as proof that my depiction of the inertial forces paralyzing statistics is not made up; and my
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description of causal inference as a "revolution" is not a fantasy. The resistance to accepting needed assumptions as "extra statistical" is alive even in 2019. Moreover, readers of this quote take it at face value that problems solved in #Bookofwhy can also be solved by
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Gelman's students w/o "wrapping them in a causal structure". This is the power of blogs; no one asks you how: eg, "Can you show us how 'traditional statistical methods" would solve problems?" People assume they somehow do. For otherwise, the all powerful science of statistics
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would be deficient, which is inconceivable, because someone would have noticed. Well, the truth is "traditional statistics" IS deficient and her obedient students cannot solve those problems without "wrapping them in a causal structure". And challenging them is no "bashing".
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