# Right Skewed Histogram: Examples and Interpretation

A histogram is a type of chart that allows us to visualize the distribution of values in a dataset.

We say that a histogram is right skewed if it has a “tail” on the right side of the distribution: Note: Sometimes a right skewed histogram is also referred to as a positively skewed histogram.

A right skewed histogram has the following two properties:

1. The peak of the distribution is on the left side. 2. The mean is greater than the median. ## What Causes a Histogram to Be Right Skewed?

A histogram is typically right skewed when there is a limit on the minimum possible value but no limit on the maximum possible value.

The most obvious real-life example of a right skewed histogram would be the distribution of income in a country.

The minimum income that a person could earn is zero dollars while there is no maximum income that a person could earn.

In general, most individuals might earn around \$40k per year but there will be a few outliers that earn several millions of dollars per year.

When we create a histogram to visualize the distribution of income, it will naturally be right skewed: ## Why is the Mean Greater than the Median in a Right Skewed Histogram?

In a right skewed histogram, the mean is greater than the median because the large values on the right “tail” of the distribution will greatly inflate the value of the mean.

As a simple example, suppose we have the following dataset that contains the income of 10 individuals:

Dataset 1: \$30k, \$35k, \$35k, \$40k, \$50k, \$55k, \$55k, \$70k, \$90k, \$110k

Here are the mean and median values of this dataset:

• Mean: \$57k
• Median: \$52.5k

Now suppose we have another dataset that contains the exact same incomes except the last value is now \$2.5 million:

Dataset 2: \$30k, \$35k, \$35k, \$40k, \$50k, \$55k, \$55k, \$70k, \$90k, \$2.5 million

Here are the mean and median values of this dataset:

• Mean: \$296k
• Median: \$52.5k

This last outlier value causes the mean income to increase significantly.

And if we plot this distribution, it would be a right skewed histogram with the \$2.5 million value located on the right “tail” of the histogram.

## The Difference Between Right Skewed & Left Skewed Histograms

The opposite of a right skewed histogram is a left skewed histogram.

This is a type of histogram that has a “tail” on the left side of the distribution: This type of histogram has the following properties:

1. The peak of the distribution is on the right side.

2. The mean is less than the median.

Notice that these are the exact opposite properties of a right skewed histogram.