Advanced Multivariate Analysis - MAT00040M
- Department: Mathematics
- Credit value: 10 credits
- Credit level: M
- Academic year of delivery: 2022-23
Related modules
Module will run
| Occurrence | Teaching period |
|---|---|
| A | Spring Term 2022-23 |
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;
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To know what sorts of methodologies should be applied to different sets of multivariate data;
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To use statistical package R to analyze multivariate data by various methodologies;
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To have a reasonable degree of familiarity with the main mathematical statistical theory of multivariate analysis;
Indicative assessment
| Task | % of module mark |
|---|---|
| Closed/in-person Exam (Centrally scheduled) | 90 |
| Coursework - extensions not feasible/practicable | 10 |
Special assessment rules
None
Indicative reassessment
| Task | % of module mark |
|---|---|
| Closed/in-person Exam (Centrally scheduled) | 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).