# Bell-shaped distribution

A bell-shaped distribution is – perhaps not surprisingly – any distribution that looks like the shape of a bell when plotted as a graph. These distributions have one mode (or peak), the mean is close to the median, and the majority of data points cluster close to the distribution’s center.

The normal distribution is the “classic” bell-shaped distribution and is sometimes called the bell-shaped distribution. However, it isn’t the only type of bell-shaped distribution: many other types of probability distributions have a bell curve shape, including the logistic distribution, t-distribution family and the Cauchy distribution. These curves are either narrower than the normal distribution — with more outliers in heavier tails or flatter with fewer outliers in thinner tails.

These distributions have one peak in the center (i.e., they are unimodal distributions) and are symmetric: if you draw a vertical line down the center of the graph, the left half will mirror the right.

## Advantages of working with a bell-shaped distribution

Bell-shaped distributions have many advantages including the fact that their spread is relatively easy to describe with standard deviations — which can be thought of as roughly the average distance data points fall from the mean. Thus, the empirical rule can be used to calculate probabilities.

## Types of bell-shaped distribution

The most well-known bell-shaped distribution is the normal distribution. Others include:

## Other types of distribution shapes

In addition to bell-shaped, we can also describe distributions as skewed, symmetric, or uniform

• Skewed distribution: is a type of distribution in which one tail is longer than the other. The “bell” is off-center and has a squashed appearance.
• Symmetric distribution: a curve where the left side of the plot mirrors the right side. These do not have to be bell-shaped. They can also be circular or triangular shaped.
• Uniform distribution: A distribution shaped like a rectangle.

## References

Top Image: Melikamp, CC BY-SA 4.0 https://creativecommons.org/licenses/by-sa/4.0, via Wikimedia Commons