California Life and Health Insurance Practice Exam

The principle that states, "The more times an event is repeated, the more predictable the outcome becomes" is known as the Law of Large Numbers. This principle is foundational in statistics and probability theory. It highlights the concept that as the sample size increases, the sample mean will get closer to the expected value or population mean.

In the context of insurance, this principle is particularly significant because it allows insurers to predict future claims based on past data. The more data (or events) an insurer has, the more accurately they can assess risk and calculate premiums. Essentially, the Law of Large Numbers underpins the stability of insurance pools and reinforces the idea that while individual outcomes may vary, the overall trend becomes more predictable with larger sample sizes.

The other concepts, while related to statistical analysis or risk assessment, do not specifically address the predictability of outcomes based on the frequency of events in the same manner that the Law of Large Numbers does. The Law of Averages, often confused with the Law of Large Numbers, is a more colloquial term and does not have the same rigorous mathematical foundation.