Module Catalogues, Xi'an Jiaotong-Liverpool University

Module Code: MTH316
Module Title: Applied Multivariate Statistics
Module Level: Level 3
Module Credits: 5.00
Semester: SEM2
Originating Department: Mathematical Sciences
Pre-requisites: MTH113

 Aims 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 StatisticsB Present the proof of the main theorems of Multivariate StatisticsC 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.
 Syllabus Graphical Representation of Multivariate data Matrix Operations. Multivariate Distributions. Multinormal Distributions. Factor Methods 1) Principal Component Analysis 2) Factor Analysis Regression 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 Clustering 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

## Assessment

 Sequence Method % of Final Mark 1 Formal Examination 85.00 2 Coursework 15.00
 Module Catalogue generated from SITS CUT-OFF: 6/5/2020 9:15:36 PM