Tests for Dependence.

Abstract

This paper is designed to provide a sound introduction for a reasonably well-informed reader who is, however, not a specialist in tests for dependence. The paper contains references to many tests but emphasizes the parametric test of independence based on Pearson's sample correlation coefficient r and certain nonparametric tests based on ranks. The ranks tests are generally preferable to the test based on r in that they have wider applicability, are much less sensitive to outlying observations, are exact under mild assumptions which do not require an underlying bivariate normal population, and have good efficiency (power) properties.

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 1979
Accession Number
ADA069567

Entities

People

  • Myles Hollander

Organizations

  • Florida State University

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force
  • Anomaly Detection
  • Body Weight
  • Cardiovascular Physiological Phenomena
  • Change Detection
  • Coefficients
  • Consumers
  • Data Science
  • Efficiency
  • High Temperature
  • Information Science
  • New York
  • Normal Distribution
  • Normality
  • Observation
  • Random Variables
  • Statistics

Readers

  • Educational Psychology
  • Statistical inference.