Machine Learning With Go

Independent and conditional probability

Two events (outcomes of experiments) are independent if the probability of one of the events in no way affects the probability of the other events. An example of independent events is the flipping of coins or the rolling of dice. On the other hand, dependent events are those events where the probability of one event influences the probability of another event. An example of dependent events is drawing cards from a deck of cards without replacement.

How can we quantify this second type of probability, which is commonly referred to as conditional probability? Symbolically, independent probabilities can be represented by P(A), which is the probability of A (where A could represent flipping a coin, rolling ...