Module Catalogues, Xi'an Jiaotong-Liverpool University   
Module Code: MTH316
Module Title: Applied Multivariate Statistics
Module Level: Level 3
Module Credits: 5.00
Academic Year: 2019/20
Semester: SEM2
Originating Department: Mathematical Sciences
Pre-requisites: MTH113
To provide a good understanding of the principles of multivariate statistics and to equip students with techniques for multivariate data analysis.
Learning outcomes 
A Understand the main principles of Multivariate Statistics

B Present the proof of the main theorems of Multivariate Statistics

C Use appropriate multivariate techniques to summarize, analyze and interpret multivariate data

D Use relevant computer packages for statistical analysis and for drawing appropriate conclusions

Method of teaching and learning 
This module will be delivered by a combination of formal lectures and tutorials.
Graphical Representation of Multivariate data

Matrix Operations.

Multivariate Distributions. Multinormal Distributions.

Factor Methods

1) Principal Component Analysis

2) Factor Analysis


1) Forward Selection and Backward Selection

2) Forward Orthogonal Least Squares

Discrimination and Classification

1) Multinomial Logistic Regression

2) Linear Discriminant Analysis

3) Support Vector Machine


1) Hierarchical Clustering

2) K-means Clustering

Delivery Hours  
Lectures Seminars Tutorials Lab/Prcaticals Fieldwork / Placement Other(Private study) Total
Hours/Semester 39    13      98  150 


Sequence Method % of Final Mark
1 Formal Examination 85.00
2 Coursework 15.00

Module Catalogue generated from SITS CUT-OFF: 8/20/2019 6:25:55 PM