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.

Ability to handle multivariate data using data reduction techniques.

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

View Now

View Now

View Now

View Now

View Now

View Now

View Now

View Now

View Now

View Now

View Now

View Now

View Now

View Now

View Now

View Now

View Now

View Now

View Now

View Now

View Now

View Now

View Now

Book Title : Introduction to Multivariate Statistical Analysis

Author : Anderson, T.W.

Edition : 3rd

Publisher : John Wiley and sons, New York

View Now

Book Title : Applied Multivariate Statistical Analysis

Author : Richard A. Johnson, Dean W. Wichern

Edition : 6th Edition

Publisher : Pearson Prentice Hall

View Now

Title : MULTIVARIATE ANALYSES INTRODUCTION

Type : Presentation

View MULTIVARIATE ANALYSES INTRODUCTION

Title : Eigenvalues and Eigenvectors

Type : Presentation

View Eigenvalues and Eigenvectors

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

View partitioning of a random vector

Title : Linear compounds and linear combinations

Type : Other

View Linear compounds and linear combinations