Number of Test Samples Needed to Obtain a Desired Bayesian Confidence Interval for a Proportion

Abstract

One recurring problem in military operational test and evaluation is determination of the number of items to test. This thesis describes a Bayesian method to determine the sample size that is needed to estimate a proportion or probability with a (1-alpha)100 confidence when a prior distribution is given to that programs, graphs, and tables to assist in finding the required sample size. These results are compared with other approaches in determining the required sample sizes that are needed to obtain a desired confidence interval for a proportion or probability.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1989
Accession Number
ADA208157

Entities

People

  • Ahmet Z. Ipekkan

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • C4I
  • Human Systems

DTIC Thesaurus Topics

  • Accuracy
  • Bayes Theorem
  • Computer Programs
  • Computers
  • Data Science
  • Distribution Functions
  • Information Science
  • Normal Distribution
  • Operations Research
  • Probability
  • Random Variables
  • Sensitivity
  • Statistical Inference
  • Statistical Samples
  • Statistics
  • Test And Evaluation
  • Theorems

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference