Social psychologist Susan Fiske has shown that common sense notions about human behavior are as often wrong as right. For example, the popular maxim opposites attract is generally false. Numerous experiments by another psychologist, Amos Tversky, have demonstrated that we-novices and Bayesian statisticians alike-are poor judges of quantity and chance. Finally, perceptual experiments, including some by Bill Cleveland himself, have shown that statisticians and other humans succumb to visual illusions when viewing statistical graphs. Martin Gardner, Richard Feynman, and the Amazing Randi have all shown how easy it is for scientists to fool themselves. Because we all think we are expert psychologists, we are at greatest risk when we study ourselves and our perceptions. Bill Cleveland has done a service to statisticians by grounding discussions about graphics in experimentation. His ideas on graphical elements, based on a series of experiments (Cleveland 1985), have influenced statistics packages (e.g., S+, STATA, and SYSTAT) and have inspired further experimentation in graphical perception (see Spence and Lewandowsky 1990). An experimental viewpoint should not diminish the work of graphic designers and others who have creative instincts for good displays. Bertin and Tufte, for example, showed that effective graphs need not be dull or lack style. We must be suspicious of any design prescription that is not supported by experimental results, however. Good design does not always lead to effective statistical graphics. Most of Cleveland's early experiments concerned graphical elements-lines, angles, areas, volumes, and colors. This article applies his thinking to graphical compositesreference grids, plotting symbols, and aspect ratios. Although its title is A Model for Studying Display Methods of Statistical Graphics, it is really more concerned with a variety of approaches to evaluating the use of these composites. While I cannot disagree with most of his conclusions about good usage, I find the model itself somewhat restrictive. Cleveland wishes to stay grounded in perceptual psychology, but the topics he discusses also involve areas of higher cognition. Cognitive psychologists such as Pinker (1990), Simken and Hastie (1987), and Kosslyn (1989) have proposed process models for graphical perceptual processing. Statisticians, on the other hand, like to think of the meaning of a graph as predefined: Construct