*68*

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

The x-axis displays the values in the dataset and the y-axis shows the frequency of each value.

Depending on the values in the dataset, a histogram can take on many different shapes.

The following examples show how to describe a variety of different histograms.

**1. Bell-Shaped**

A histogram is bell-shaped if it resembles a “bell” curve and has one single peak in the middle of the distribution. The most common real-life example of this type of distribution is the normal distribution.

**2. Uniform**

A histogram is described as “uniform” if every value in a dataset occurs roughly the same number of times. This type of histogram often looks like a rectangle with no clear peaks.

**3. Bimodal**

A histogram is described as “bimodal” if it has two distinct peaks. We often say that this type of distribution has multiple modes – that is, multiple values occur most frequently in the dataset.

**Related:** What is a Bimodal Distribution?

**4. Multimodal**

A histogram is described as “multimodal” if it has more than two distinct peaks.

**Related:** What is a Multimodal Distribution?

**5. Left Skewed**

A histogram is left skewed if it has a “tail” on the left side of the distribution. Sometimes this type of distribution is also called “negatively” skewed.

**Related:** 5 Examples of Negatively Skewed Distributions

**6. Right Skewed**

A histogram is right skewed if it has a “tail” on the right side of the distribution. Sometimes this type of distribution is also called “positively” skewed.

**Related:** 5 Examples of Positively Skewed Distributions

**7. Random**

The shape of a distribution can be described as “random” if there is no clear pattern in the data at all.

**Additional Resources**

The following tutorials provide more information on how to describe distributions.

Left Skewed vs. Right Skewed Distributions

What is a Symmetric Distribution?

What is a Relative Frequency Histogram?

How to Estimate the Mean and Median of Any Histogram