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###### Course Contents

Review of matrix algebra, notations of multivariate distributions. The multivariate normal distribution and its properties. Linear compound and linear combinations. Estimates of mean vector and covariance matrix. The wishart distribution and its properties. The joint distribution of sample mean vector and the sample covariance matrix. The Hotclling’s T2 distribution. Tests of hypothesis and confidence intervals for mean vectors. One sample and two sample procedures.

###### Course Synopsis

Ability to handle multivariate data using data reduction techniques.

###### Course Learning Outcomes

On successful completion of the course the students will be able to  handle the multivariate data,  differentiate between multivariate techniques and their univariate versions.

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###### Hotelling T2 test by Matthew E. Clapham

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Book Title : Introduction to Multivariate Statistical Analysis
Author : Anderson, T.W.
Edition : 3rd
Publisher : John Wiley and sons, New York
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Book Title : Applied Multivariate Statistical Analysis
Author : Richard A. Johnson, Dean W. Wichern
Edition : 6th Edition
Publisher : Pearson Prentice Hall
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Title : MULTIVARIATE ANALYSES INTRODUCTION
Type : Presentation

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Title : Eigenvalues and Eigenvectors
Type : Presentation

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Title : Fun with Vectors
Type : Presentation

View Fun with Vectors

Title : Introduction to the square root of a 2 by 2 matrix
Type : Other

View Introduction to the square root of a 2 by 2 matrix

Title : partitioning of a random vector
Type : Other

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Title : Linear compounds and linear combinations
Type : Other

View Linear compounds and linear combinations