Graphics are an important means of communicating experimental data and results. There is evidence, however, that many of the graphics printed in scientific journals contain errors, redundancies, and lack clarity. Perhaps more important, many graphics fail to portray data at an appropriate level of detail, presenting summary statistics rather than underlying distributions. We seek to aid investigators in the production of high-quality graphics that do their investigations justice by providing the reader with optimum access to the relevant aspects of the data. The depiction of by-subject data, the signification of pairing when present, and the use of symbolic dimensionality (graphing different symbols to identify relevant subgroups) and small multiples (the presentation of an array of similar graphics each depicting one group of subjects) to portray stratification are stressed. Step-by-step instructions for the construction of high-quality graphics are offered. We hope that authors will incorporate these suggestions when developing graphics to accompany their manuscripts and that this process will lead to improvements in the graphical literacy of scientific journals. We also hope that journal editors will keep these principles in mind when refereeing manuscripts submitted for peer review.