What characterizes a normal distribution in statistics?

A normal distribution is characterized by its symmetric, bell-shaped curve, which means that the data is evenly distributed around the mean. This symmetry indicates that most of the observations cluster around the central peak, with probabilities tapering off as you move away from the center in either direction.

In a normal distribution, the mean, median, and mode are all equal, occurring at the center of the distribution. The bell shape illustrates that there are fewer extreme values when compared to values closer to the mean, which is a key aspect that helps in many statistical analyses, such as hypothesis testing and confidence interval estimation.

The other options describe distributions that do not align with the properties of a normal distribution, emphasizing why the symmetric, bell-shaped characteristic is essential to identifying it accurately.