Abstract

Graphic data visualization is essential to Exploratory Data Analysis and precedes any statistical analysis. Box plots are one of the most widely used graphical representation to show descriptive statistics of data in a sample and to represent multiple comparisons. This graphic, however, if careless used can markedly distort data interpretations, and for this reason in this paper we describe box plot pitfalls and show several ways to improve them using R programming flexibility. By adding jittered raw data, histograms and density curves graphic variants can be produced, which had been described in recent literature with other names such as violin plots, pirate plots, raincloud plots, beanplots, sinaplots, among others. We also present the app Extended Boxplot Graphics that facilitates the use of potent graphic flexibilities of R without mastering the programming language. With this app in a simple way several enhanced variations of box plots can be produced to represent scientific results. Citation: Denis, D. & Ramirez-Arrieta, V.M. 2020. Si una imagen vale mas que mil palabras: ?cuanto puede decir un grafico de cajas? Revista Jard. Bot. Nac. Univ. Habana 41: 57-69. Article history : Received 3 June 2020. Accepted: 22 June 2020. Online: 26 September 2020. Editor: Jose Angel Garcia-Beltran.

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