I feel like this paragraph might be a little necessary for someone who haven’t read the bayes rule intro, but on the other hand is a bit off-topic in this context and quite distracting, as it raises questions which are not part of this “discussion”; mainly, questions regarding how to approach “one-off” events.
Say, what if I can’t quantify the outcome of my decision so nicely like in the case of a bet? What if I need to decide whether to send Miss Scarlet to prison or not based on these likelihood probabilities?
I’m going to take the role of the “undergrad” here and try to interpret this in the following way:
Given that a hypothesis is true—but it is unknown to be true—it is far more likely to come by a “statistically significant” result indicating it is wrong, than it is likely to come by a result indicating that another hypothesis is significantly more likely.
In simpler words—it is far easier to “prove” a true hypothesis is wrong by accident, than it is to “prove” that an alternative hypothesis is superior (a better estimator of reality) by accident.
Would you consider this interpretation accurate?