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Comment by Richard Zander (richard-zander) on 12 interesting things I learned studying the discovery of nature's laws · 2022-02-28T19:53:53.185Z · LW · GW

Oh, and statistics is not math, it's physics. You can test the results of statistics against the real world, but math is merely consistent.

Comment by Richard Zander (richard-zander) on 12 interesting things I learned studying the discovery of nature's laws · 2022-02-27T22:10:12.532Z · LW · GW

Math is not physics. I'm not sure what math is. I kind of like Gisin's support of intuitive math. I agree that the next billion digits of pi mean nothing real, also that there should be some constructivist dimension to the infinities in math (e.g. renormalization).

Comment by Richard Zander (richard-zander) on “Who’s In Charge? Free Will and the Science of the Brain” · 2021-09-16T13:07:43.725Z · LW · GW

We are free to think we are free. Freedom is the opiate of the optimists, so be sour and you will be free of freedom.

Comment by Richard Zander (richard-zander) on Review of A Map that Reflects the Territory · 2021-09-13T14:27:46.090Z · LW · GW

Regarding digits of pi, N. Gisin promotes the constructivist idea that certain mathematical expressions mean nothing in that they do not relate to anything real. One cannot make a scientific hypothesis involving them. The hundred-billionth twenty digit sequence of pi is smaller than the Plank length.

Comment by Richard Zander (richard-zander) on Is it true that most studies in Kahneman's 'Thinking fast and slow' are not replicable and the book is largely not supported by evidence? · 2021-06-30T20:07:19.188Z · LW · GW

Try books by Gerd Gigerenzer (search on Amazon). I particularly like his Empire of Chance, about different schools of probability analysis.  Bounded Rationality is pretty good, too. The difference between Gigerenzer's and Tversky's attitudes is not particularly impressive (they apparently hate each other, even though one is dead). One is decision making when in a hurry (Gigerenzer) and the other is decision-making with insufficient data (Tversky) (or maybe it's the other way around, tedious stuff). Discussions of biases is fascinating by both authors.