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: |
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Assessment Summary: | EX 100% |
Assessment Detail: |
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Supplementary Assessment: |
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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
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Notes:
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