Introduction

If, to paraphrase Richard Hamming's remark about computing, the goal of policy analysis is insight, not numbers, then clearly one of the most important challenges of policy analysis is to communicate the insights it provides to those who need them. Such insights can include an appreciation of the overall degree of uncertainty about the “bottom line” conclusions, an understanding of which sources of uncertainty and which modeling assumptions are critical to those conclusions and which are not, and an understanding of the extent to which plausible alternative assumptions can change the conclusions that are reached. The insights obtained will ultimately be qualitative in nature, even if the models they derive from are quantitative. This means it is incumbent on the analyst to find ways to present quantitative results in a manner that will most clearly communicate the information they contain and aid users in developing the appropriate qualitative insights. Most experienced analysts believe that graphical techniques play an indispensable role in this process, yet the use of graphics to communicate uncertain information has been the focus of remarkably little attention. This chapter is concerned with exploring some of the alternatives that are available for graphic presentation of uncertain quantitative information, and some of the necessary tradeoffs between simplicity and sophistication, particularly in choosing the dimensionality of information to present.