Statistical Measures, Probability Densities, and Mathematical Models for Stochastic Measurements.

Abstract

Statistical measures, probability densities, and mathematical modeling techniques useful in the analysis of stochastic measurements are summarized. Univariate measures are given for average, dispersion, skewness, and kurtosis. Probability Densities include: Normal, Student t, Cauchy, Gamma, Exponential, Chi-square, F, Rayleigh, Maxwell, Log-normal, Beta, Uniform, and Arc-sine. Measures of interdependence between two variables include simple correlation, autocorrelation, cross-correlation, rank correlation, point biserial correlation, tetrachoric correlation, and coefficients of contingency. Measures of interdependence among several variables include multiple correlation, marginal correlation, conditional correlation, canonical correlation, and auto and cross-correlation for ensembles of measurements. Mathematical modeling techniques include factor analysis and both regression and analysis of variance formulated as the general linear hypothesis model. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1976
Accession Number
ADA037483

Entities

People

  • Robert G. Merkle

Organizations

  • Flight Dynamics Laboratory

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Air Force
  • Analysis Of Variance
  • Cross Correlation
  • Data Analysis
  • Data Mining
  • Data Science
  • Ergodic Processes
  • Factor Analysis
  • Governments
  • Information Processing
  • Information Science
  • Mathematical Models
  • Probability
  • Probability Density Functions
  • Random Variables
  • Statistical Analysis
  • Stochastic Processes

Fields of Study

  • Mathematics

Readers

  • Approximation Theory.
  • Calculus or Mathematical Analysis
  • Regression Analysis.