What characterizes a normal distribution in statistics?

A normal distribution is characterized by being a bell-shaped curve that is symmetrically centered around the mean. In this distribution, the mean, median, and mode are all equal and located at the center of the curve. The shape of the curve indicates that as you move away from the mean, the probabilities of values occurring decrease, resulting in a gradual slope downwards on either side. This property makes the normal distribution an important concept in statistics, as many statistical methods and tests are based on the assumption that the data follows a normal distribution.

The bell shape reflects that most of the data points are concentrated around the mean, with fewer observations occurring as you move further away from the mean in either direction. This characteristic is essential in various statistical applications, such as hypothesis testing and confidence interval estimation, where the normal distribution serves as a basis for inferential statistics.