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:

right skewed histogram

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.

peak of right skewed histogram

2. The mean is greater than the median.

mean vs median in right skewed histogram

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:

real life example of right skewed histogram

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

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