What does conditional probability refer to?

Conditional probability specifically relates to the likelihood of an event given that another event has already occurred. It signifies how the probability of one event is affected by the occurrence of a previous event. For example, if you want to know the probability of it raining tomorrow (event A) given that it has rained today (event B), you are using conditional probability.

This concept is fundamental in statistics and helps in scenarios where events are not independent—meaning the occurrence of one event influences the probability of the other. This understanding is crucial in areas such as risk assessment, decision-making processes, and predictive modeling, where the interdependencies of events must be taken into account.

The other options do not encapsulate the essence of conditional probability. One option discusses the joint occurrence of events, which pertains to a different aspect of probability analysis. Another focuses on independence, while another suggests a reversed relationship that does not align with the definition of conditional probability at all.