A box plot, otherwise known as a box and whisker plot, is a graph that displays a summary of a large amount of data in five numbers. These numbers include the median, upper quartile, lower quartile, minimum data value and maximum data value. Like with many statistical graphs, the box plot method has both its advantages and disadvantages.
Handles Large Data Easily
Due to the five number data summary, a box plot is able to 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 that is too unmanageable for other graphs, such as line plots or stem and leaf plots.
Exact Values Not Retained
The issue with handling such large amounts of data in a box plot is that the exact values and details of the distribution of results are not retained. A box plot shows only a simple summary of the distribution of results, so that it can be quickly viewed and compared with other data. For a thorough, more detailed analysis of data a box plot should be used in combination with another statistical graph method, such as a histogram.
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.
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. An outlier is an obscure result that can be detected by extending the minimum and maximum data values to a maximum of 1.5 times the inter-quartile range. Any results of data that fall outside of the minimum and maximum values are considered outliers, which are easy to determine on a box plot graph.