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Can the vague meanings of probability terms such as doubtful, probable, or likely be expressed as membership functions over the [0, 1] probability interval? A function for a given term would assign a membership value of /ero to probabilities not at all in the vague concept represented by the term, a membership value of one to probabilities definitely in the concept, and intermediate membership values to probabilities represented by the term to some degree. A modified pair-comparison procedure was used in two experiments to empirically establish and assess membership functions for several probability terms. Subjects performed two tasks in both experiments: They judged (a) to what degree one probability rather than another was better described by a given probability term, and (b) to what degree one term rather than another better described a specified probability. Probabilities were displayed as relative areas on spinners. Task a data were analyzed from the perspective of conjoint-measurement theory, and membership function values were obtained for each term according to various scaling models. The conjoint-measurement axioms were well satisfied and goodness-of-fit measures for the scaling procedures were high. Individual differences were large but stable. Furthermore, the derived membership function values satisfactorily predicted the judgments independently obtained in task b. The results support the claim that the scaled values represented the vague meanings of the terms to the individual subjects in the present experimental context. Methodological implications are discussed, as are substantive issues raised by the data regarding the vague meanings of probability terms. Most people, including expert forecasters, generally prefer communicating their uncertain opinions with nonnumerical terms such as doubtful, probable, slight chance, very likely, and so forth, rather than with numerical probabilities. On anecdotal grounds, the imprecision of nonnumerical terms is preferred to the precision of probability numbers for at least two reasons: First, opinions are generally not precise and therefore, the claim goes, it would be misleading to represent them precisely. For example, commenting that numbers denote authority and a precise understanding of relations, a committee of the U.S. Na-This research was supported by Contract MDA 903-83-K-0347 from the U.S. Army Research Institute for the Behavioral and Social Sciences to the L. L. Thurstone Psychometric Laboratory, University of North Carolina at Chapel Hill. The views, opinions, and findings contained in this paper are those of the authors and should not be construed as an official Department of the Army position, policy, or decision. Barbara Forsyth is now at Ohio University. We thank Samuel Fillenbaum for numerous helpful discussions throughout the course of the work, and James Cox, Brent Cohen, Samuel Fillenbaum, and Jaan Valsiner for comments on a previous draft of this article.

Despite much disagreement regarding how probabilistic information is best communicated, virtually no research has been done to determine what communication modes people prefer or what factors affect their communication preferences. To address these issues, we did a survey of 442 graduate and undergraduate students in several specialties and universities. Some group differences emerged, but overall, 34% expressed preference for both conveying and receiving information about uncertainty in numerical rather than verbal form , 30% expressed the opposite preferences, and 35% indicated that they preferred to receive such information numerically but to convey it verbally. Generally, respondents who endorsed the use of verbal information said that it is easier to use , as well as more natural and personal. Those preferring numerical information said that it is more precise. Virtually all respondents, however, evidenced a willingness to use the opposite of their initially preferred mode if the situation should warrant it. The willingness to switch from one mode to another was said to depend on the level of precision implied by the data and the importance of the issue, as was suggested by Budescu and Wallsten (1987). These results may be helpful in structuring risk communication strategies.The importance of risk communication has increased dramatically in recent years as the public has become more aware of and interested in environmental and medical issues that affect individuals and society. Although much has been written about the best modes for communicating with individuals about uncertainty, little research has been aimed at determining what modes people prefer or what factors affect their preferences. We present survey results relevant to these questions.To set the stage , we will review the issues very briefly. Although decision and risk analysis are frequently done in terms of estimated or judged probabilities (Morgan & Henrion, 1990;von Winterfeldt & Edwards, 1986), the risk communication literature is virtually unanimous in stating that the presentation of statistical information alone is insufficient for communicating with the public (Fisher, 1991; Linnerooth-Bayer & Wahlstroorn, 1991;National This research was supported by National Science Foundation Grants BNS8608692 and BNS8908554 . We thankAnn Fisher and Baruch Fischhoff for comments on an earlier draft . R.Z . is in the Department of Marketing at Penn sylvania State . Correspondence should be addressed to T . S. Wallsten , Department of Psychology, Univer sity of North Carolina, Chapel Hill , NC 27599 -3270.Research Council, 1981;Slovic, 1986) or even for experts' communications to decision makers (Ruckelshaus, 1984). For example, The National Research Council (1981) wrote that It is usually dangerous for messages to characterize the overall level of uncertainty quantitatively, as might be done by describing statistical confidence intervals. In most situations expert assessments have multiple sources of uncertainty , and statistical measures do not adequat...