https://www.amazon.com/Experimental-Physics-Principles-Pract...

https://www.amazon.com/Optimal-Design-Experiments-Study-Appr...

https://www.amazon.com/Statistical-Analysis-Experimental-Dov...

https://www.amazon.com/dp/0471718130

https://ocw.mit.edu/courses/physics/8-13-14-experimental-phy...

https://www.youtube.com/playlist?list=PL7145A9AA4BAF35FC

ML can be useful, but it is getting too much attention. Far more hype than the value it actually provides in many domains, IMHO.

Yes, I know that there are folks that deal with vast amounts of data with inscrutable relationships where you need fancy algorithms to make progress. But seriously, most problems just don't need it, and many folks would be better off with mastering basic statistics and data analysis.

It's fascinating how far you can get with basic stuff. My favorite? Statistics for Experimenters, by George E. Box. It's like a secret weapon! https://www.amazon.com/Statistics-Experimenters-Design-Innov...