ABSTRACT
Good graphics are informative, effective and flexible. Graphics can be attractive and encourage discussion, they can be more insightful and convincing than text. Different types of graphics highlight different features in datasets. A group of graphics of the same type, but with different formatting and scaling, may also pick out a range of different aspects of data. It is useful to experiment with different options: growing or shrinking plots, changing their aspect ratios, reordering categories, and trying out different binwidths or bandwidths. Graphics may look different because of how they are drawn—the formatting, scaling, and colouring. Using many graphics avoids possibly misleading effects in individual displays due to this. In the case of Graphical Data Analysis (GDA) there can be downsides due to badly chosen graphics, overloaded graphics, poorly organised groups of graphics, over-interpretation of graphics, and apophenia. GDA is, of course, also affected if data are inadequate, a problem for all statistical and data analyses.
