Although R is not menu-driven – taking more time to learn than packages in common use – it allows far more control over presentation than such packages. This contention is supported through analysis of, and reference to, real data and the way they are commonly presented in the literature. Graphical presentation is also often poor, probably because of reliance on the ‘defaults’ in conveniently available menu-driven packages, such as Excel, not specifically designed for statistical analysis. The authors’ view is that graphs are sometimes unnecessary, where the relevant information is better conveyed in a simple sentence or commentary on a table. Part of the motivation for writing the text was dissatisfaction with much of what is to be found in this literature. Full details of the data sets and R code used are available as separate supplementary files. Copious illustrative examples using real data are provided and placed in their archaeological context. The text illustrates how such plots can be obtained using the open source software system R the other graphical methods covered are kernel density estimates, ternary diagrams and correspondence analysis.
The archaeological literature is permeated with the use of simple statistical graphics, such as histograms, pie charts, barplots, scatterplots and boxplots.
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