Languages and Designs for Probability Judgment*

The semantics and syntax of the Bayesian language and the language of belief functions are described and compared and some of the designs for probability judgment afforded by the two languages are investigated.

Abstract

Theories of subjective probability are viewed as formal languages for analyzing evidence and expressing degrees of belief. This article focuses on two probability langauges, the Bayesian language and the language of belief functions (Shafer, 1976). We describe and compare the semantics (i.e., the meaning of the scale) and the syntax (i.e., the formal calculus) of these languages. We also investigate some of the designs for probability judgment afforded by the two languages.