What I meant was that for h_1%, you're going to wind up with probabilities in the area of like, 1.2e-34, very quickly, if the coin is a fair one. The update pr

What I meant was that for h_1%, you're going to wind up with probabilities in the area of like, 1.2e-34, very quickly, if the coin is a fair one. The update process is adjusting via multiplication, and for a really bad hypothesis, that's going to bring its probability dramatically close to zero without that many trials. Even though the absolute difference between 1e-4 and 1-e34 hypothesis feels smallish when you look on a linear scale from 0-1, a 1-e34 is a lot 'stickier'. Your explanation has the benefit of being a better explanation; my goal was just to explain where the inertia was hiding.