THE CHI-SQUARE TEST OF GOODNESS OF FIT FOR A BIVARIATE NORMAL DISTRIBUTION.

Abstract

A brief summary of the bivariate normal distribution is given: estimating the five parameters, determining the two regression lines, transforming the original random variables to achieve independence, testing the null hypothesis that the correlation coefficient is zero, and describing the contour ellipses. The Pearson Chi-Square Goodness of Fit Criterion is described for testing the null hypothesis that the parent population of a random sample of paired random variables is bivariate normal. (Author)

Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1966
Accession Number
AD0646141

Entities

People

  • Carl B. Bates

Organizations

  • Naval Surface Warfare Center Dahlgren Division

Tags

DTIC Thesaurus Topics

  • Chi Square Test
  • Coefficients
  • Computing-Related Activities
  • Data Science
  • Information Science
  • Interdisciplinary Science
  • Mathematical Analysis
  • Mathematics
  • Normal Distribution
  • Random Variables
  • Statistical Analysis
  • Statistical Samples
  • Statistics

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.