title: The box plot: a simple visual method to interpret data.
abstract: Exploratory data analysis involves the use of statistical techniques to identify patterns that may be hidden in a group of numbers. One of these techniques is the "box plot," which is used to visually summarize and compare groups of data. The box plot uses the median, the approximate quartiles, and the lowest and highest data points to convey the level, spread, and symmetry of a distribution of data values. It can also be easily refined to identify outlier data values and can be easily constructed by hand. We apply box plots to tabular data from two recently published articles to show how readers can use box plots to improve the interpretation of data in complex tables. The box plot, like other visual methods, is more than a substitute for a table: It is a tool that can improve our reasoning about quantitative information. We recommend that the box plot be used more frequently.
authors.affiliation: Centers for Disease Control, Atlanta, Georgia.
authors.forename: D F
authors.initials: DF
authors.lastname: Williamson
authors.forename: R A
authors.initials: RA
authors.lastname: Parker
authors.forename: J S
authors.initials: JS
authors.lastname: Kendrick
mesh_terms: D000428:Alcohol Drinking / Q000502:physiology; D001835:Body Weight; D003327:Coronary Disease / Q000209:etiology; D003626:Data Display; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D008297:Male; D008433:Mathematics; D005082:Physical Exertion; D012044:Regression Analysis; D012107:Research Design; D012306:Risk; D012907:Smoking / Q000503:physiopathology