Nassim Taleb: We should retire the notion of standard deviation

he's really lost the plot. :(

Why, it is pretty good in describing probability distributions. What we should retire are idiots, who assume that it predicts an outcome of the next event.

While the mean deviation as presented is slightly nicer than sigma for intuitive purposes, it isn't as appropriate (iirc) for statistical tests on normal distributions and t-distributions.

More importantly, it doesn't fix the real problem, which is that the mean and standard deviation don't tell you everything you need to know about a data set, but often people like to pretend they do. It's not rare to read a paper in the soft sciences which might have been improved if the authors had reported the skewness, kurtosis, or similar data which could shed light on the phenomenon they're investigating. These latter statistics can reveal, for instance, a bimodal distribution, which could indicate a heterogeneous population of responders and non-responders to a drug, and that's just one example.

I'm not a statistician, so some of this might be a bit off.

Like this?

"But it is not just journalists who fall for the mistake: I recall seeing official documents from the department of commerce and the Federal Reserve partaking of the conflation, even regulators in statements on market volatility. What is worse, Goldstein and I found that a high number of data scientists (many with PhDs) also get confused in real life."

It doesn't tell us what happened, it just asserts that it did in certain contexts. It doesn't cite the paper he presumably wrote with Goldstein (which Goldstein?) about it. I feel like I'm getting a summary of an abstract with all the citations missing.