Figure 1. Box plot of data from the Michelson experiment
In descriptive statistics, a box plot or boxplot is a method for demonstrating graphically the locality, spread and skewness groups of numerical data through their quartiles.[1] In addition to the box on a box plot, there can be lines (which are called whiskers) extending from the box indicating variability outside the upper and lower quartiles, thus, the plot is also called the box-and-whisker plot and the box-and-whisker diagram. Outliers that differ significantly from the rest of the dataset[2] may be plotted as individual points beyond the whiskers on the box-plot.
Box plots are non-parametric: they display variation in samples of a statistical population without making any assumptions of the underlying statistical distribution[3] (though Tukey's boxplot assumes symmetry for the whiskers and normality for their length). The spacings in each subsection of the box-plot indicate the degree of dispersion (spread) and skewness of the data, which are usually described using the five-number summary. In addition, the box-plot allows one to visually estimate various L-estimators, notably the interquartile range, midhinge, range, mid-range, and trimean. Box plots can be drawn either horizontally or vertically.
^C., Dutoit, S. H. (2012). Graphical exploratory data analysis. Springer. ISBN 978-1-4612-9371-2. OCLC 1019645745.{{cite book}}: CS1 maint: multiple names: authors list (link)
^Grubbs, Frank E. (February 1969). "Procedures for Detecting Outlying Observations in Samples". Technometrics. 11 (1): 1–21. doi:10.1080/00401706.1969.10490657. ISSN 0040-1706.
^Richard., Boddy (2009). Statistical Methods in Practice : for Scientists and Technologists. John Wiley & Sons. ISBN 978-0-470-74664-6. OCLC 940679163.
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