Tangentially: I am really enjoying the book "All of Statistics" as a reference for better understanding things like histograms, kernel density functions, etc, and their parameters.
Aren't you refererring to "All of non-parametric statistics"? https://www.amazon.com/All-Nonparametric-Statistics-Springer...
Either way I can't recommend these books enough, really opened my eyes to the inner workings of statistics in a rigorous yet accessible way.
I am actually most interested non-parametric statistics, especially to "reformulate" as many statistical tests as possible using a small number of robust primitives (like the bootstrap.) More pointers in that direction would be very welcome :-)
Tangentially: I am really enjoying the book "All of Statistics" as a reference for better understanding things like histograms, kernel density functions, etc, and their parameters.
https://www.amazon.com/All-Statistics-Statistical-Inference-...