A box plot, also known as a box and whisker plot, is a type of graph that displays a summary of a large amount of data in five numbers. These numbers include the median, upper quartile, lower quartile, minimum and maximum data values. Like with many statistical graphs, the box plot method has advantages and disadvantages.

#### TL;DR (Too Long; Didn't Read)

Box and whisker plots handle large data effortlessly, but they do not retain the exact values and the details of the results of the distribution. These graphs allow a clear summary of large amounts of data.

## Handles Large Data Easily

Due to the five-number data summary, a box plot can handle and present a summary of a large amount of data. A box plot consists of the median, which is the midpoint of the range of data; the upper and lower quartiles, which represent the numbers above and below the highest and lower quarters of the data and the minimum and maximum data values. Organizing data in a box plot by using five key concepts is an efficient way of dealing with large data too unmanageable for other graphs, such as line plots or stem and leaf plots.

## Exact Values Not Retained

The box plot does not keep the exact values and details of the distribution results, which is an issue with handling such large amounts of data in this graph type. A box plot shows only a simple summary of the distribution of results, so that it you can quickly view it and compare it with other data. Use a box plot in combination with another statistical graph method, like a histogram, for a more thorough, more detailed analysis of the data.

## A Clear Summary

A box plot is a highly visually effective way of viewing a clear summary of one or more sets of data. It is particularly useful for quickly summarizing and comparing different sets of results from different experiments. At a glance, a box plot allows a graphical display of the distribution of results and provides indications of symmetry within the data.

## Displays Outliers

A box plot is one of very few statistical graph methods that show outliers. There might be one outlier or multiple outliers within a set of data, which occurs both below and above the minimum and maximum data values. By extending the lesser and greater data values to a max of 1.5 times the inter-quartile range, the box plot delivers outliers or obscure results. Any results of data that fall outside of the minimum and maximum values known as outliers are easy to determine on a box plot graph.