Skewness is a statistical measure that describes the asymmetry or lack of symmetry in a distribution of data. It indicates the degree and direction of skew (departure from horizontal symmetry) in a set of values. A perfectly symmetrical distribution has a skewness of zero, meaning the distribution is balanced on both sides of its central point.

Positive skewness indicates that the distribution's tail is skewed to the right, meaning that it has a longer or fatter tail on the right side. In contrast, negative skewness indicates a distribution with a longer or fatter tail on the left side.

Skewness is a valuable measure in statistics and data analysis because it provides insights into the shape of a distribution. Understanding skewness helps analysts and researchers assess the nature of data distributions and make more informed decisions about the appropriateness of certain statistical methods.