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MA40090: Multivariate data analysis

[Page last updated: 22 May 2025]

Academic Year: 2025/26
Owning Department/School: Department of Mathematical Sciences
Credits: 6 [equivalent to 12 CATS credits]
Notional Study Hours: 120
Level: Masters UG & PG (FHEQ level 7)
Period:
Semester 2
Assessment Summary: EX 100%
Assessment Detail:
  • Examination (EX 100%)
Supplementary Assessment:
Like-for-like reassessment (where allowed by programme regulations)
Requisites: Before taking this module you must have taken first-year Algebra and first-year Probability & statistics.
Learning Outcomes: On completing the course, students should be able to:
* select and apply an appropriate technique for the analysis of multivariate data to look for structure in such data or to achieve dimensionality reduction;
* carry out multivariate inferential techniques.


Content: Revision of relevant matrix algebra.
Exploratory and graphical analysis of multivariate data.
Principal components analysis.
Classification: linear and quadratic discrimination and logistic regression.
Topics selected from:
Tree-based methods. Ensemble methods. Support vector machines. Factor analysis. Multidimensional scaling. Cluster analysis.

Skills: Numeracy T/F A
Problem Solving T/F A
Written and Spoken Communication F

Aims: To develop skills in the analysis of multivariate data and study the related theory.

Course availability:

MA40090 is Optional on the following courses:

Department of Mathematical Sciences
  • USMA-AFM14 : MMath(Hons) Mathematics (Year 4)
  • USMA-AAM15 : MMath(Hons) Mathematics with Study year abroad (Year 4)
  • USMA-AKM15 : MMath(Hons) Mathematics with Year long work placement (Year 5)

Notes:

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