Skewness: Skewness refers to the asymmetry or lack of symmetry in a data distribution. It indicates whether the majority of data points are concentrated on one side or if they are evenly distributed.
Kurtosis: Kurtosis measures the shape of a data distribution's tails (ends). A high kurtosis value indicates heavy tails, meaning there are more extreme values, while low kurtosis means lighter tails.
Outliers: Outliers are extreme values that greatly differ from other data points in a distribution. They can significantly affect measures like the mean and may distort our understanding of the overall pattern.