What characterizes a normal distribution?

A normal distribution is characterized by its symmetric shape, where the data points are distributed evenly around a central value, specifically the mean. This symmetry means that the left half of the distribution mirrors the right half, creating a bell-shaped curve. In a normal distribution, most of the data points cluster around the mean, which is also the median and mode, resulting in a higher frequency of occurrences near the mean compared to the tails of the distribution.

This configuration indicates that values close to the mean are more common, while values further away are less frequent, creating the characteristic bell shape. Therefore, the correct choice emphasizes this key attribute of normal distributions, highlighting both the symmetry and the concentration of data around the mean.

Understanding this concept is critical in statistics and quality control because it allows practitioners to apply various statistical analyses and make informed decisions based on the predictable characteristics of data that follows this distribution.