[psoy]

This is silly in my view, and bordering on pseudoscience-level writing. It's not a random historical accident that we use these quantities.

Variance / stdev appear all over probability and statistics. For example, in this famous Stats 101 theorem: https://en.wikipedia.org/wiki/Chebyshev%27s_inequality

[jerf]

You are mistaking him for someone who is ignorant and slagging the best practices; in fact, he's incredibly knowledgeable and experienced and slagging best practices. I'm not saying he's guaranteed to be right about everything, but he's made rather a lot of money by turning his criticisms into actions, and that's a pretty tall bar to leap.

I'll say it again because I can already hear the reply buttons clicking... I'm not saying he's right about everything or that money is the only measure of rightness. I'm just saying that it's definitely a measure worth paying attention to, and definitely puts you on the experienced side rather than the ignorant side. If it was just chance, it's still interesting.

[psoy]

Sounds like Appeal to Authority to me: https://en.wikipedia.org/wiki/Argument_from_authority

FWIW I am also someone who knows what he's talking about, as I am a seasoned professional in the same line of work.

This guy's accomplishments don't make the Chebyshev inequality any less true (nor all the other theorems involving variance), so I don't see how he can claim something like this and be taken seriously by people in the field.

[jerf]

Because it's not about the theorems being wrong, it's about people using them in impractical ways.

The Central Limit Theorem is true. Full stop. It can't be wrong. However, in the real world, a lot fewer things are truly Gaussian than may initially meet the eye. It doesn't make the CLT "false", it just means that people who apply it too carelessly are making a mistake. Standard deviation is a thing, but that doesn't make it the right thing for a given task.

A lot of people apply statistics inappropriately. It's hardly their fault, it's basically what they are taught. I remember seeing my wife take her biology statistics courses, which at times seemed to be a course in which you would repeatedly calculate p-values. Just that, over and over; calculate this p-value. Calculate that p-value. Calculate this other p-value. Say "Yes" if it's less than 0.05 and "No" if it's greater. Now do it again. And again. And again. Certainly numbers went in one end of the calculator and came out the other, but did they mean anything? If not, it's not because the p-value isn't "true", just not even remotely as useful as the course was implicitly teaching.

(Yes, words were said about how it wasn't the only useful thing, but the actions spoke loud and clear. Compute p-value. Say yes if below 0.05. Say no if above. Repeat. The current problems all the fields are having with statistics aren't that surprising if you look back to the beginning.)

[vacri]

Looks like you're committing your own fallacy there. Jerf's topic is Taleb's level of authority, not the veracity of the statement of the article. How is it "argument from authority" when the argument is trying to establish how much authority the actor has in the first place?

The comment even has two separate disclaimers saying that Taleb might not be right about this, just that he has enough experience to be worth listening to on the subject.

[reso]

It's not really appeal to authority. He's not claiming that Taleb is right because of who he is, rather that we shouldn't dismiss him out of hand because he's very accomplished and credible.