What is the correct interpretation of P(A^c)?

The interpretation of P(A^c) refers to the probability of the complement of event A, which is indeed the probability of event A not occurring. In probability theory, the complement of an event encompasses all outcomes in the sample space that do not belong to the event.

When you express the complement of A, denoted as A^c, it highlights all possible scenarios where A does not take place. Thus, P(A^c) quantifies the likelihood of these scenarios, providing a meaningful way to analyze the outcomes where a particular event is absent. This understanding is central to many statistical calculations and helps in determining the overall probabilities more effectively.

The other options refer to different concepts in probability. For example, determining the probability of event A occurring would focus on P(A), not its complement. The total probability of all events, while related to the entire sample space, does not specifically address the complement. Lastly, the combined probability of multiple events pertains to the outcomes involving more than one event, rather than focusing solely on the absence of a single event.