What characteristic defines a normal distribution?

A normal distribution is fundamentally characterized by its bell-shaped curve and symmetry about the mean. This means that the data is evenly distributed around the center point, with most of the data points clustering near the mean and probabilities tapering off symmetrically towards the extremes.

In a standard normal distribution, the left side of the curve mirrors the right side perfectly, which is a hallmark of this statistical concept. This symmetry suggests that the mean, median, and mode of the distribution coincide at the center of the distribution. Hence, the defining characteristic that distinguishes a normal distribution from others is this bell-shaped and symmetric nature.

The other options suggest various types of distributions that do not reflect the properties of a normal distribution. For example, skewed distributions are not symmetrical, and uniform distributions lack the bell shape characteristic of normal distributions. Positively skewed distributions are concentrated on the left with a long tail extending to the right, which is also contrary to the definition of a normal distribution.