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.

Read more about left skewed histograms in this tutorial.

**Additional Resources**

The following tutorials provide additional information about histograms:

How to Estimate the Mean and Median of Any Histogram

How to Estimate the Standard Deviation of Any Histogram

How to Describe the Shape of Histograms