What is the Empirical Rule used for in statistics?

The Empirical Rule is a fundamental principle in statistics that helps understand the distribution of data, particularly when the data follows a normal distribution. Specifically, the Empirical Rule states that about 68% of the data falls within one standard deviation of the mean, approximately 95% within two standard deviations, and nearly 99.7% within three standard deviations. This allows statisticians and analysts to make inferences about the data's spread and identify the typical range within which most data points will lie.

By using the Empirical Rule, one can gain insights into how much of the dataset lies within various ranges around the mean, which is key for comparisons, interpretations, and predictions based on the data at hand. It also provides a quick way to visualize where data points are likely to fall and how concentrated they are around the average, making it an invaluable tool for understanding the overall shape and characteristics of a dataset.