Inference for an Experiment based on Repeated Majority Votes.

Abstract

Consider an experiment which consists of n independent Bernoulli sequences, each of which is randomly terminated at either the kth success or the kth failure, whichever comes first. The goals are to make inferences about the per trial probability of success, as well as the probability that a sequence is terminated with a success. The latter is equivalent to the probability that if 2k-1 trials are accumulated, the majority will be successes. Various estimators are investigated, and the results of an ESP experiment fitting this scheme are examined.

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Document Details

Document Type
Technical Report
Publication Date
Oct 15, 1985
Accession Number
ADA161241

Entities

People

  • Jessica Utts

Organizations

  • Stanford University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Asymptotic Normality
  • Calculators
  • Chi Square Test
  • Dacron
  • Data Science
  • Estimators
  • Information Science
  • Maximum Likelihood Estimation
  • Multivariate Analysis
  • New York
  • Probability
  • Random Variables
  • Statistical Algorithms
  • Statistical Analysis
  • Statistics
  • Stochastic Processes
  • United States

Fields of Study

  • Mathematics

Readers

  • Approximation Theory.
  • Regression Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference