Displaying Uncertainty: Investigating the Effects of Display Format and Specificity

We conducted four studies regarding the representation of probabilistic information. Experiments 1 through 3 compared performance on a simulated stock purchase task, in which information regarding stock profitability was probabilistic. Two variables were manipulated: display format for probabilistic information (blurred and colored icons, linguistic phrases, numeric expressions, and combinations) and specificity level (in which the number and size of discrete steps into which the probabilistic information was mapped differed). Results indicated few performance differences attributable to display format; however, performance did improve with greater specificity. Experiment 4, in which participants generated membership functions corresponding to three display formats, found a high degree of similarity in functions across formats and participants and a strong relationship between the shape of the membership function and the intended meaning of the representation. These results indicate that participants can successfully interpret nonnumeric representations of uncertainty and can use such representations in a manner similar to the way numeric expressions are used in a decision-making task. Actual or potential applications of this research include the use of graphical representations of uncertainty in systems such as command and control and situation displays.

[1]  Christopher D. Wickens,et al.  The Interaction of Spatial and Color Proximity in Aircraft Stability Information Displays , 1988 .

[2]  C. Eriksen,et al.  Effects of noise letters upon the identification of a target letter in a nonsearch task , 1974 .

[3]  Kevin B. Bennett,et al.  Emergent Features and Graphical Elements: Designing More Effective Configural Displays , 1993 .

[4]  A. Tversky,et al.  Judgment under Uncertainty: Heuristics and Biases , 1974, Science.

[5]  David V. Budescu,et al.  Dyadic decisions with numerical and verbal probabilities , 1990 .

[6]  A. Kramer,et al.  Perceptual organization and focused attention: The role of objects and proximity in visual processing , 1991, Perception & psychophysics.

[7]  R. Hogarth.  Insights in Decision Making , 1990 .

[8]  David V. Budescu,et al.  Decisions based on numerically and verbally expressed uncertainties. , 1988 .

[9]  Ido Erev,et al.  Understanding and using linguistic uncertainties , 1988 .

[10]  Alex T. Pang,et al.  Approaches to uncertainty visualization , 1996, The Visual Computer.

[11]  I. Erev,et al.  Verbal versus numerical probabilities: Efficiency, biases, and the preference paradox☆ , 1990 .

[12]  Robert M. Hamm,et al.  Selection of verbal probabilities: A solution for some problems of verbal probability expression. , 1991 .

[13]  R. Hogarth,et al.  Ambiguity and Uncertainty in Probabilistic Inference. , 1985 .

[14]  Charles J. Holahan,et al.  Effects of Visual Distraction on Reaction Time in a Simulated Traffic Environment , 1978 .

[15]  Shawn P. Curley,et al.  The center and range of the probability interval as factors affecting ambiguity preferences , 1985 .

[16]  Christopher D. Wickens,et al.  The Proximity Compatibility Principle: Its Psychological Foundation and Relevance to Display Design , 1995, Hum. Factors.

[17]  Anthony D. Andre,et al.  Displaying Uncertainty in Advanced Navigation Systems , 1998 .

[18]  Roland W. Scholz,et al.  Qualitative aspects of decision making , 1997 .

[19]  Ann M. Bisantz,et al.  Utilizing Graphical Formats to Convey Uncertainty in a Decision Making Task , 2000 .

[20]  Amnon Rapoport,et al.  Measuring the Vague Meanings of Probability Terms , 1986 .

[21]  C. Eriksen,et al.  Temporal changes in the distribution of attention in the visual field in response to precues , 1987, Perception & psychophysics.

[22]  Christopher D. Wickens,et al.  Mixing and Matching Lower-Level Codes for Object Displays: Evidence for Two Sources of Proximity Compatibility , 1996, Hum. Factors.

[23]  Alan M. MacEachren,et al.  VISUALIZING UNCERTAIN INFORMATION , 1992 .

[24]  Nils-Eric Sahlin,et al.  Decision making with unreliable probabilities , 1983 .

[25]  David V. Budescu,et al.  A review of human linguistic probability processing: General principles and empirical evidence , 1995, The Knowledge Engineering Review.

[26]  Mica R. Endsley,et al.  Toward a Theory of Situation Awareness in Dynamic Systems , 1995, Hum. Factors.

[27]  D. Medin,et al.  Decision making from a cognitive perspective , 1995 .

[28]  Johannes Hönekopp,et al.  Precision of probability information and prominence of outcomes: A description and evaluation of decisions under uncertainty. , 2003 .

[29]  Alex T. Pang,et al.  Visualizing Geometric Uncertainty of Surface Interpolants , 1996, Graphics Interface.

[30]  Mica R. Endsley,et al.  Measurement of Situation Awareness in Dynamic Systems , 1995, Hum. Factors.

[31]  D. Krantz,et al.  The use of statistical heuristics in everyday inductive reasoning , 1983 .

[32]  Amnon Rapoport,et al.  Direct and indirect scaling of membership functions of probability phrases , 1987 .

[33]  D. Budescu,et al.  Processing Linguistic Probabilities: General Principles and Empirical Evidence , 1995 .

[34]  Susan S. Kirschenbaum,et al.  Effects of Graphic and Verbal Probability Information on Command Decision Making , 1994 .