> You're the event and you have some sort of expectation about your outcomes. The event is the test grade. I am not a test grade, I am a person. If it's proble

> You're the event and you have some sort of expectation about your outcomes. The event is the test grade. I am not a test grade, I am a person. If it's problematic that I'm taking the test, how about I tell my friend that I didn't study, and my friend give a 50% probability that I fail? > you can peg your chances to pass at 50%, but that doesn't tell you anything about the chances of the rest of the class. I wasn't talking about the rest of the class, I was talking about the probability that the professor would give me of failing the test. Is your probability theory so weak that it refuses to make a prediction for that? What are we supposed to use instead, our gut feelings? > If you observe all possible outcomes of an event, you can deterministically predict its outcomes. If you observe sufficiently many outcomes of a stochastic event, you can probabilistically predict its outcomes. The laws of probability apply just as well to deterministic and stochastic events. There is no useful distinction between a deterministic event of which we have partial knowledge (enough to assign a good "probability" to each outcome), and stochastic events of which we have full knowledge. As an example, take a board game that uses dice. How does the gameplay change if we replace the dice with a seeded RNG picking numbers from 1-6? Moreover, think of your favorite (classical) stochastic process. What if it's secretly deterministic, but only you know enough information -- an impractically large amount of information? What changes?