Multivariate Test Procedures for Unknown Means When Sampling from Bivariate Normal Populations.

Abstract

AL TESTS), MATHEMATICAL PREDICTION, PROBABILITY DENSITY FUNCTIONS, MATRICES(MATHEMATICS)NORMAL DENSITY FUNCTIONS, BIVARIATE ANALYSIS, STATISTICAL INFERENCEThe report investigates and presents statistical testing procedures when sampling from bivariate normal populations for which inferences are drawn concerning unknown means. Multivariate hypothesis testing procedures for testing for unknown means in the bivariate case are presented. Pitfalls and shortcomings of using separate hypotheses for each unknown mean are discussed. An example for the bivariate case is shown whereby two different conclusions can be reached using the same experimental data. One set of conclusions is made using the multivariate procedure (correct procedure), and a completely different set of conclusions is made using the classical hypothesis testing procedure for each unknown mean. (Author)

Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1973
Accession Number
AD0762110

Entities

People

  • Charles E. Colvin

Organizations

  • United States Army Aviation and Missile Command

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Bivariate Analysis
  • Data Science
  • Experimental Data
  • Functions (Mathematics)
  • Hypotheses
  • Information Science
  • Mathematical Analysis
  • Mathematics
  • Normal Density Functions
  • Probability
  • Probability Density Functions
  • Random Variables
  • Sampling
  • Statistical Algorithms

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference