Recall that in the distribution of a dataset, if the left half of the graph is not a mirror image of the right half, the data is said to be skewed.  

There are three types of skewness. If a graph extends to the left side forming a longer tail on the left, it is called negatively skewed. If a graph extends to the right side forming a longer tail on the right, it is said to be positively skewed. Finally, a graph with symmetric or normal distribution has zero skewness.

A graph representing negatively skewed data usually has the mean and median to the left side of the mode.  

Conversely, a positively skewed dataset has the mean and median to the right side of the mode.  

For example, the distribution of annual income among residents of a city, a large number of people on the lower-income side, indicates positive skewness. Whereas, the distribution of students’ scores on an easy exam, with fewer students scoring lower scores, shows negatively skewed data.