Left-skewed (also known as negatively skewed) refers to the shape of a distribution where most data points tend to be concentrated on the right side, while few data points are spread out towards the left side. The tail of the distribution extends towards smaller values.
Related terms
Right-Skewed: The opposite of left-skewed; it refers to distributions where most data points tend to be concentrated on the left side, while few data points are spread out towards the right side.
Symmetric Distribution: In symmetric distributions, data points are evenly distributed around its center point without any skewness towards either direction.
Outliers: Outliers are extreme values that significantly differ from other observations in a dataset and can affect the skewness of a distribution.