Weighing Evidence: The Design and Comparison of Probability Thought Experiments.

Abstract

The assessment of probability on the basis of evidence is viewed as a thought experiment that yields an expression of degree of belief. Theories of subjective probability are viewed as tools or languages for analyzing evidence and expressing degree of belief. This article focuses on two probability languages: the classical Bayesian language and the language of belief functions. 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 analyze the designs of thought experiments afforded by the two languages and discuss their implications. (Author)

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1983
Accession Number
ADA131475

Entities

People

  • Amos Tversky
  • Glenn Shafer

Organizations

  • Stanford University

Tags

Communities of Interest

  • Biomedical
  • C4I
  • Ground and Sea Platforms
  • Human Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Applied Psychology
  • Human Factors Engineering
  • Information Processing
  • Information Science
  • Information Systems
  • Jet Propulsion
  • Language
  • Military Research
  • Navy
  • Operations Research
  • Probability
  • Probability Distributions
  • Psychology
  • Seabed
  • Semantics
  • Social Sciences
  • Systems Engineering

Readers

  • Computational Linguistics
  • Statistical inference.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Translation