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Skewness is a way to describe the of a distribution.
A distribution is positively skewed if it has a “tail” on the right side of the distribution:
Note: Sometimes positively skewed distributions are also called “right skewed” distributions.
In this article we share 5 examples of positively skewed distributions in the real world.
Example 1: Distribution of Income
The distribution of individual incomes in the U.S. is right-skewed, with most individuals earning between $20k and $40k per year but with a long right tail of households that earn much more.
Example 2: Distribution of Scores on a Difficult Exam
The distribution of scores on any particularly difficult exam will be positively skewed with most students scoring around some mean value with a few outlier students scoring much higher.
Example 3: Distribution of Pet Ownership
The distribution of the number of pets that households own in any particular city is likely to be right skewed because most households have either 0 or 1 pet, but there are many outlier households that have 7, 8, 9+ pets that cause the distribution to be right skewed.
Example 4: Distribution of Points Scored
The distribution of points scored per game by NBA players is right skewed because most players score between 5-10 points per game, but there are some outliers who score 25+ points per game that cause the distribution to be right skewed.
Example 5: Distribution of Movie Ticket Sales
The distribution of tickets sold per movie is right skewed because most movies are duds and sell relatively few total tickets. However, some blockbuster hits sell millions of tickets, which causes the distribution of movie ticket sales to be right skewed.
5 Examples of Negatively Skewed Distributions