[jasonwatkinspdx]

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.

[actusual]

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

[jasonwatkinspdx]

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.

[disgruntledphd2]

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.

[fhsm]

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

[stevegalla]

> 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.

[BeetleB]

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.

[tajd]

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