Bayesian Data Analysis of Gambling Preferences

Abstract

The paper emphasizes the use of Bayesian data analysis for experiments with choices among gambles. In an introductory example, the method is illustrated by a comparison of two learning theories. Special problems arise with the analysis of data from decision making experiments which assume deterministic choice models which cannot be handled by Bayesian analyses. Several ways around these difficulties are suggested, discussed, and demonstrated on two sets of data from choice-among-gambles experiments.

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Document Details

Document Type
Technical Report
Publication Date
Nov 02, 1973
Accession Number
AD0770584

Entities

People

  • Dirk Wendt

Organizations

  • University of Michigan

Tags

Communities of Interest

  • Autonomy
  • Human Systems

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Bayesian Inference
  • Bayesian Networks
  • Books
  • Data Analysis
  • Data Mining
  • Data Science
  • Data Sets
  • Information Processing
  • Information Science
  • Machine Learning
  • New York
  • Probability
  • Probability Distributions
  • Psychology
  • Statistics
  • Theses

Readers

  • Computational Modeling and Simulation
  • Systems Analysis and Design
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference