ST323: Multivariate Statistics

Lecturer(s)

Dr Dario Spano & Dr Nikos Zygouras

Important: If you decide to take ST323 you cannot then take ST412. Bear this in mind when planning your module selection. Recall: a BSc.MMORSE student must take at least 120 CATS, of level 4+ modules over their 3rd & 4th years.

Prerequisite(s): ST208 Mathematical Methods or equivalent, ST218 Mathematical Statistics A, ST219 Mathematical Statistics B

This module runs in Term 1.

Aims: Multivariate data arises whenever several interdependent variables are measured simultaneously. This occurs frequently in many areas: in medicine, in the social and environmental sciences and in economics. The analysis of such multidimensional data often presents an exciting challenge that requires new statistical techniques which are usually implemented using computer packages. This module aims to give you a good understanding of the geometric and algebraic ideas that these techniques are based on, before giving you any chance to try them out on some real data sets.

Objectives: By the end of the course students will be able to:

  • Carry out a principal components analysis and use it to summarise high dimensional data.
  • Use linear discriminant analysis to solve simple classification problems.
  • Understand the theory of the multivariate normal distribution.
  • Perform multivariate hypothesis tests and construct confidence regions.

Books:

Krzanowski, W.J., Principles of Multivariate Analysis : a user’s perspective, Oxford: Clarendon 2000.

Johnson, R.A. and Wichern, D.W., Applied Multivariate Statistical Analysis, 6th edition Pearson International 2007.




 

You may also wish to see:

ST323: Resources for Current Students (restricted access)