What principle suggests that larger data sets lead to more reliable statistics?

The principle that larger data sets lead to more reliable statistics is known as the Law of Large Numbers. This statistical theorem states that as the size of a sample increases, the sample mean (or average) will get closer to the expected value (or population mean). In essence, this means that with a larger number of observations, random fluctuations are minimized, and the results become more stable and accurate.

When applying this principle in various fields, such as insurance or economics, it shows how collecting more data can lead to more reliable estimates and predictions. For instance, in insurance, a larger pool of claims data allows for better forecasting of risk and loss, enabling companies to set premiums more effectively.

In contrast, smaller data sets can lead to variability and sometimes misleading outcomes, emphasizing the importance of the Law of Large Numbers in statistical analysis.