Verbal vs. Numerical Processing of Subjective Probabilities

Decision Making Under Uncertainty (Advances in Psychology 16)
Zimmer, A. C.
Elsevier Science Publishers B.V.
The Netherlands

Ubiquitously people have to address the problem of uncertainty. The main focus of this article is an investigation of how people represent their knowledge about the uncertainty of events or regularities, and how they process this knowledge in order to make decisions in order to share their knowledge. In a first experiment it is asked how people gather information about frequencies of events and how this knowledge is interfered with the response mode, numerical vs. verbal estimates, they are required to use. The least interference occurs if the subjects are allowed to give verbal answers. From this it is concluded that processing knowledge about uncertainty by means of verbal expression imposes less mental work load on the organism than does numerical processing. Possibility theory is used as a framework for modeling the individual usage of verbal categories. The 'elastic' constrains on the verbal expressions for every single subject are determined in a further experiment by means of sequential testing. The results from this experiment are used to suggest a simple mechanism underlying the "availability" heuristic. In further experiments it is shown that the superiority of the verbal processing of knowledge about uncertainty quite generally reduces persistent biases reported in the literature: conservatism and negligence of regression. In a final experiment about predictions on a real-life situation it turns out that in a numerical forecasting task subjects restricted themselves to those parts of their knowledge which are numerical. On the other hand subjects in a verbal forecasting task accessed verbally as well as numerically stated knowledge. The conjecture is made that the superiority of the verbal mode in representing and in processing knowledge about uncertainty is due to "share-ability" (Freyd, in press)constrains which have evolved in the history of humankind and might even be phylogenetically determined.

The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education