Mean vector and covariance matrix
Mean vector and covariance matrix
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Course Material
- Aspects of multivariate analysis, Assumptions behind multivariate structure.
- Organization of Data, Difference between univariate and multivariate statistical techniques.
- Matrix algebra and vector algebra
- Mean vector and covariance matrix
- maximum inequalities and maximization methods.
- Multivariate normal distribution, inferences about mean vector
- Estimation of the mean vector and covariance matrix.
- comparisons of several multivariate means
- Multivariate analysis of variance (MANOVA)
- Principal components analysis,
- Factor analysis,
- Discriminant analysis,
- Cluster analysis.
- Multidimensional scaling.
- Canonical Correlation
- software application
- Chapters 16
- Department Statistics
- Teacher
Qasim Ramzan
