Ohio Assessments for Educators (OAE) Mathematics Practice Exam 2026 - Free Practice Questions and Study Guide

Skewness is a statistical measure that describes the asymmetry of a data distribution. When a distribution is skewed, it indicates that the data are not symmetrically distributed around the mean. This can manifest as a longer tail on one side of the distribution compared to the other.

For instance, if a distribution has a positive skew (right-skewed), this means that there are a greater number of lower values with some extreme high values that pull the mean to the right. Conversely, a negative skew (left-skewed) implies that there are more higher values with some extreme low values that pull the mean to the left.

Understanding skewness is vital because it helps in making inferences about the data's distribution, such as determining the appropriate statistical tests to use or understanding the potential impact of outliers. This understanding is fundamentally tied to the concept of symmetry, where a symmetric distribution would exhibit a skewness of zero, indicating that the data is evenly distributed about the mean.