Sample Size for Correlation Estimates

Abstract

This thesis examines the classical measure of correlation (Pearson's R) and two nonparametric measures of correlation (Spearman's r and Kendall's tau) with the goal of determining the number of samples needed to estimate a correlation coefficient with a 95% confidence level. For Pearson's R, tables, graphs, and computer programs are developed to find the sample number needed for a desired confidence interval size. Nonparametric measures of correlation (Spearman's ra and Kendall's tau) are also examined for appropriate sample numbers when a specific confidence interval size desired.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1989
Accession Number
ADA219810

Entities

People

  • Kemal Salar

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Weapons Technologies

DTIC Thesaurus Topics

  • Computer Programs
  • Computers
  • Confidence Limits
  • Covariance
  • Data Science
  • Distribution Functions
  • Information Science
  • New York
  • Nonparametric Statistics
  • Normal Distribution
  • Operations Research
  • Probability
  • Probability Distributions
  • Random Variables
  • Sampling
  • Statistical Samples
  • Statistics

Fields of Study

  • Mathematics

Readers

  • Statistical inference.