SOME COMPONENTS OF PROBABILISTIC INFERENCE.

Abstract

In most studies of probabilistic inference, subjects have behaved conservatively, i.e., they have revised their probability estimates less than the amount prescribed by Bayes's theorem. This study attempts to shed further light on the conservatism effect by analyzing the process of inductive inference into two components, and determining the effects on conservatism of these two components. One component is deduction: determining the probabilistic relationships between the datum observed and the hypotheses being considered. The second component is combination of the data: combining the effects of individual items of data in order to make an inference based on all the data observed.

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1966
Accession Number
AD0650223

Entities

People

  • Lawrence D. Phillips

Organizations

  • University of Michigan

Tags

DTIC Thesaurus Topics

  • Conservatism
  • Hypotheses
  • Mathematics
  • Political Ideologies
  • Probability

Readers

  • Computational Modeling and Simulation
  • Statistical inference.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference