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.
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.
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.
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?
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.
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.
The shape of a distribution can be described as “random” if there is no clear pattern in the data at all.
The following tutorials provide more information on how to describe distributions.