Taleb is... not a good source for learning statistics. Start with Wasserman. Taleb says obvious and well known things using his own invented terminology in order to cast himself as some sort of contrarian genius. It's not that he's wrong, it's that the insights he hawks are banal. That's why his readership base are insight porn book junkies not people actually trying to learn statistical methods.

"insight porn books" is going in my "objects you've been searching for titles for" Notion list.

Yeah, I think I first heard it in relation to Malcolm Gladwell and it's just so apt at capturing everything wrong with that category of book. I mean he's a skillful writer, and it's definitely entertaining stuff. But if you flip into critical mode and do comparative research vs authoritative sources, you start seeing how vapid it is really fast.

When I read Fooled by Randomness I found it useful. Not groundbreaking work, but it drew some nice analogies between statistical distributions and human's over-certainty.

Would love to see that list or any other on which this choice descriptor finds itself.

> Start with Wasserman

If you're referring to "All of Statistics" by Wasserman, then there are some significantly easier textbooks to learn statistics from. Depending on the program, "All of Statistics" is a book used by senior undergrads or grad students. Are there more mathematical heavy stats books, yes, but this isn't a casual read for someone who is trying to learn statistics either.

I like "Probability and Statistics for Engineering and the Sciences" by Devore as an intro book. It covers the basics of probability distributions, maximum likelihood and method of moments estimation, ANOVA, and linear regression. Pre-requisite knowledge is probably multivariable calculus, matrix multiplication, determinants, and eigenvalues.

Devore's book is great. It's sad it gets many negative reviews. In my experience, there are two types of people:

1. Those who want a statistics book to be like a math book: Fewer words and more equations.

2. Those who want a wordy book with little math

Devore's book is in between, which is why I think both camps tend to hate it. It has a decent amount of math, and has quite a bit of text. The text is invaluable: You get information about common rules of thumb. You get insights on why the technique works. Etc.

And the examples/problems are great. So many of them are from real papers/books. You're not working on some contrived example, but on real world problems.

If you do have his books then the reference lists in the back provide a good starting point for further reading.

I have read this book and want to leave an anti-recommendation here. It's a poorly edited mess and makes at least one blatant mathematical error.

More broadly, let me leave a Taleb anti-recommendation. His entire shtick is yelling that traditional statisticians have ignored heavy-tailed random variables in their modeling and that he has special insight into the nature of tail risk (perhaps along with a few select other people, like Mandelbrot).

But this is manifestly not the case. In fact, if you go through his Amazon reviews page, you can find him leaving positive reviews several years ago on all the books written by traditional statisticians that he learned about heavy-tailed randomness from!

link to his Amazon reviews page?

Scroll back to the early 2010s: https://www.amazon.com/gp/profile/amzn1.account.AHMHNR4MRTDL...

For a more detailed critique, see Robert Lund, Revenge of the White Swan, The American Statistician Vol. 61, No. 3 (Aug., 2007). Accessible through your favorite Russian website.

If you want a better book on heavy-tailed randomness, I like Didier Sornette's Critical Phenomena in Natural Sciences (subtitled Chaos, Fractals, Selforganization and Disorder: Concepts and Tools).

Revenge of the White Swan also appears available on ResearchGate:

https://www.researchgate.net/publication/4741329_Revenge_of_...

This feels only slightly more legitimate than recommending the 538 blog as a statistical authority.

calling someone's book suggestion an "advertisement" is rude, and inaccurate. taleb wouldn't pay anyone to suggest his book when he could instead just show up here and insult everyone for free.

I didn’t mean it strictly literally. The original comment was a thoughtless namedrop of a brand new book (which means by tautology it’s irrelevant to the topic at hand) and doesn’t have a shred of reasoning behind it. So, functionally, it’s a billboard advertising Taleb’s book.

I am aware that the Cult of Taleb means that people are willing to advertise his work for free.

Not mentioned, not cited in the paper. That's shocking.

Edit: the word "tail" appears nowhere in the paper, in any context. I'm beyond shocked now.

Because this was well known to statisticians long before Taleb talked about it?

That would be my suspicion as to why it isn't there.

Quite plausible. Extreme Value theory [1] appears to have been codified by the 1960s, and one of the main theorems is credited “to Fréchet (1927), Ronald Fisher and Leonard Henry Caleb Tippett (1928), Mises (1936) and Gnedenko (1943)” [2]. ETA: And the second theorem of Extreme Value Analysis is from the mid 1970s. [3]

1. https://en.wikipedia.org/wiki/Extreme_value_theory

2. https://en.wikipedia.org/wiki/Fisher–Tippett–Gnedenko_theore...

3. https://en.wikipedia.org/wiki/Pickands–Balkema–De_Haan_theor...

My stats training was in the 90s and we absolutely covered leptokurtic things.

The book by Leadbetter, Lindgren and Rootzen is good too if a bit dated.

This is subsumed in the robust estimation section.