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Multivariate Analysis: Course outline

Multivariate analysis (MVA) is based on the statistical principle of multivariate statistics, which involves observation and analysis of more than one statistical outcome variable at a time.

Course Outline

  • Multivariate Normal Distribution
  • Wishart distribution and their properties
  • Hotelling’s T2 – Distribution
  • Methods of Estimation
  • Maximum Likelihood and least squares
  • Multivariate Hypothesis testing
  • Likelihood ratio test.
  • One sample and multi-sample hypotheses
  • Principal Component Analysis
  • Factor Analysis,
  • Discriminant Analysis
  • Cluster analysis
  • Path analysis
  • Multivariate Analysis of Variance (MANOVA)

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