What characteristic of a distribution indicates that values are concentrated toward one of the extremes?

The characteristic of a distribution that indicates values are concentrated toward one of the extremes is skew. Skewness refers to the asymmetry of a distribution. When a distribution is skewed, it means that there is a long tail on one side of the distribution, which causes most values to cluster toward one end.

In a positively skewed distribution, for instance, most data points fall on the left side, while the tail extends to the right. Conversely, in a negatively skewed distribution, the bulk of the data is on the right, with the tail stretching to the left. This phenomenon allows one to quickly identify which direction the concentration of values is leaning, highlighting the imbalance in the distribution.

Other types of distributions mentioned, such as uniform distribution, normal distribution, and bimodal distribution, do not exhibit this concentration toward one extreme in the same manner. A uniform distribution is characterized by all outcomes being equally likely, hence having no concentration. A normal distribution is symmetrical and bell-shaped, indicating that data is centered around the mean without skew toward any extreme. A bimodal distribution shows two peaks or modes, indicating the presence of two distinct groups within the data, rather than a concentration toward an extreme.