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Advanced Multivariate Analysis - MAT00040M

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  • Department: Mathematics
  • Module co-ordinator: Prof. Degui Li
  • Credit value: 10 credits
  • Credit level: M
  • Academic year of delivery: 2020-21

Related modules

Co-requisite modules

  • None

Prohibited combinations


Module will run

Occurrence Teaching cycle
A Spring Term 2020-21

Module aims

The aim of the module is to introduce students to the main ideas and their justifying theories of multivariate statistical analysis.

Module learning outcomes

  • To have developed a knowledge and good understanding of models and methods for multivariate data;

  • To have a good degree of familiarity with the main methodologies and techniques of multivariate analysis;

  • To know what sorts of methodologies should be applied to different sets of multivariate data;

  • To use statistical package R to analyze multivariate data by various methodologies;

  • To have a reasonable degree of familiarity with the main mathematical statistical theory of multivariate analysis;

Assessment

Task Length % of module mark
Essay/coursework
Coursework
N/A 10
University - closed examination
Advanced Multivariate Analysis
2 hours 90

Special assessment rules

None

Reassessment

Task Length % of module mark
University - closed examination
Advanced Multivariate Analysis
2 hours 100

Module feedback

Current Department policy on feedback is available in the student handbook. Coursework and examinations will be marked and returned in accordance with this policy.

Indicative reading

Richard Johnson, Dean Wichern. Applied Multivariate Statistical Analysis. Prentice Hall, ISBN 0-1312-1973-1. (SF 2 JOH)

Brian Everitt. An R And S-plus Companion To Multivariate Analysis. Springer, 2005. (SF 2 EVE).

C Chatfield and A J Collins. Introduction to Multivariate Analysis. Chapman and Hall (SF 2 CHA).

K V Mardia, J T Kent and J M Bibby. Multivariate Analysis. Academic Press (SF2 MAR).

T.W. Anderson. An introduction to multivariate statistical analysis. New York : Wiley, 1984.

M G Kendall. Multivariate Analysis. Arnold (SF 2 KEN).



The information on this page is indicative of the module that is currently on offer. The University is constantly exploring ways to enhance and improve its degree programmes and therefore reserves the right to make variations to the content and method of delivery of modules, and to discontinue modules, if such action is reasonably considered to be necessary by the University. Where appropriate, the University will notify and consult with affected students in advance about any changes that are required in line with the University's policy on the Approval of Modifications to Existing Taught Programmes of Study.