I wonder if it is because simulation can often allow you to get around needing P&S techniques in general? Or maybe it is that (Neural Network) ML models allow you to often approximate the things you might do with P&S in terms of making decisions?
No real point, I just think it is interesting.
There is a separate topic "Data & Statistics" that has quite some relevant titles.
Also, I think the interest in probability theory has only recently grown with the advent of generative AI. I'm expecting more interest in the future.
Edit: also, the site seems to miss some nice gems, most likely because they are not traditionally published books: "Probabilistic Artificial Intelligence" is freely available on Arxiv, and was discussed on Hacker News in March 2025 [1].
* Probability and Statistics for Engineers and Scientists, that showed me how to calculate various percentages and p values and what does statistical testing really means * How to Lie with Statistics, that showed me how easily you can manipulate the numbers to get what you want out of them
Another neat one, albeit niche, is Directional Statistics. Turns out, doing stats on angles and directions is less trivial than it sounds!