Advanced Regression and Multivariate Analysis - MAT00094M
Module summary
This module introduces various models and methods for multivariate data analysis as well as data-driven nonparametric models and methods.
Related modules
Pre-requisite modules
Prohibited combinations
Module will run
| Occurrence | Teaching period |
|---|---|
| A | Semester 1 2025-26 |
Module aims
This module introduces various models and methods for multivariate and multilevel data analysis, as well as data-driven nonparametric models and methods.
Module learning outcomes
By the end of the module, students should be able to:
1. Work with different models for multivariate or multilevel data, and nonparametric models.
2. Apply the main techniques of multivariate and multilevel data analysis, and nonparametric estimation methods, and pick appropriate techniques to apply to different types of data.
3. Use the statistical package R to analyse multivariate and multilevel data.
Additional learning outcome for M-level students:
4. Carry out self-directed analysis of more complex problems requiring more advanced techniques or analysis methods (for M-level students)
Module content
This module can be split into two parts. Part (i) covers topics in multivariate and multilevel data analysis, to be taught in the first seven weeks; and part (ii) introduces some commonly-used nonparametric models and methods including the kernel and local polynomial estimations, to be taught in the last three weeks.
Indicative assessment
| Task | % of module mark |
|---|---|
| Closed/in-person Exam (Centrally scheduled) | 100.0 |
Special assessment rules
None
Indicative reassessment
| Task | % of module mark |
|---|---|
| Closed/in-person Exam (Centrally scheduled) | 100.0 |
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
T.W. Anderson. An Introduction to Multivariate Statistical Analysis. New York : Wiley, 2003.
C. Chatfield and A. J. Collins. Introduction to Multivariate Analysis. Chapman and Hall, 1980.
B. Everitt. An R and S-plus Companion to Multivariate Analysis. Springer, 2005.
J. Fan and I, Gijbels. Local Polynomial Modelling and Its Applications. Chapman and Hall/CRC, 1996.
K. V. Mardia, J. T. Kent and J. M. Bibby. Multivariate Analysis. Academic Press, 1979.
H. Goldstein. Multilevel Statistical Models. Wiley, 2010