Great talk! I’m amazed how well "n = 1 observation" worked. I guess it was an observation of a handful of squares.
I work on survey statistics for measuring carbon in agricultural soil (for quantifying carbon credits), so it was fun to see analogs in your talk. I’m interested in Bayesian approaches to survey inference, and it seems your solution could be cast in that way, as a simple random sample of molecules from your beaker.
Thanks for the fun talk.