What characteristic does a skewed distribution have?

A skewed distribution is characterized by having a long tail on one side, which indicates that the data is not evenly distributed around the mean. This asymmetry can manifest in two different forms: right skew (positive skew) and left skew (negative skew). In a right-skewed distribution, the tail on the right side is longer or fatter, indicating that there are a number of unusually high values pulling the mean to the right. Conversely, in a left-skewed distribution, the tail on the left side is extended, reflecting the presence of unusually low values.

The presence of this long tail on one side is crucial for understanding how the majority of data points are grouped and highlights the departure from normal distribution characteristics, where data is symmetrically distributed around the mean. This feature has significant implications for statistical analysis, including the interpretation of measures like mean and median, which can be affected by the skewness of the data set.