Board Thread:General Discussion/@comment-26006155-20200107155350/@comment-32182236-20200205021412

Alright.

The theorem itself comes from this:https://brilliant.org/wiki/bayes-theorem/

P(A) is the probability that event A happens. In the case of Bayes' Theorem, we're talking about the probability that our hypothesis is true, which is why I changed A to H.

The ¬ symbol is a negator:So P(¬A), would be the chances of event A having not happened.

P(A|B) refers to the probability that event A happened, given the fact that event B happened.

P(E) must be separated into both the case that the hypothesis is true, and it's found [P(H)*P(E|H)], and the case that the hypothesis is false, and it's found [P(¬H)*P(E|¬H)] We then add the two together.

So that's what it all means.

I then gave another method of writing the formula, where I just used four variables used to calculate the probability we're looking for, and explained what each of them meant.

Which one was easier for you to understand? My first post, or my second?