Conditional Probability and Independence
Conditional probabilities measure the probability of events given some knowledge.
Prior probabilities measure the probabilities of events before we consider our additional knowledge.
Posterior probabilities are probabilities that result from using our additional knowledge.
The chain rule relates intersection with conditionalization (important to NLP)
Independence and conditional independence of events are two very important notions in statistics.