Okay, so I sent a confession of love to a girl detailing several reasons and coming up with a 90% probability that I will be with her together for my whole life.
But I then thought that I was supposed to be a frequentist and not a Bayesian, because I cannot start up 100 samples of me and her in a virtual machine and build prediction intervals for breakup time.
Is this true? I always thought that probability is utterly useless if it cannot allow you to, say, claim that a coin you never flipped has a probability 1/6. On the other hand it seems wrong to suppose, say, that my probability of being forever with my beloved would decrease due to a revelation that she is a spy for the NSA.
What exactly is the difference between frequentists and Bayesians on probabilities of unknown events? My frequentist stat teacher simply handwaves about it and say that we just call it a 90% "confidence" without daring to call it a probability and violating Þe Olde Frequentist School. That seems so unrigorous, and besides when calculating my 90% "confidence", I used formulas with, guess what, $Pr(...)$ in them.