Bayes Formula-Can someone help me see the light?

I have read that there is a secret “tree” formula to use when applying bayes formula? Can someone share this with me and help me see the light? This is the one area of quant I am struggling with. An example with the answer would be much appreciated. Thanks guys!

Someone posted me one the other day. It is also in the CFAi book, the tree formula.

E=Event I=Information P(E|I) = P(I|E)/P(I) * P(E) Just remember “I over I” in the ratio. And since you have “I” in the denominator, start with “I” in the numerator. That’s the mnemonic that I use. Remember how to apply the total probability rule in calculating P(I). Say there are two outcomes of the event. P(I) = P(I|E1)P(E1) + P(I|E2)P(E2) If you’re only given P(E1), then the complement is 1-P(E1). All you’re doing with this formula is going backwards and adjusting your probability of a certain even. If you discover a new piece of information, how does it change the probability of that event?