ST405 Half Unit
Multivariate Methods
This information is for the 2020/21 session.
Teacher responsible
Dr Yunxiao Chen
Availability
This course is available on the MPhil/PhD in Statistics, MSc in Data Science, MSc in Marketing, MSc in Statistics, MSc in Statistics (Financial Statistics), MSc in Statistics (Financial Statistics) (ÐÓ°ÉÂÛ̳ and Fudan), MSc in Statistics (Financial Statistics) (Research), MSc in Statistics (Research), MSc in Statistics (Social Statistics) and MSc in Statistics (Social Statistics) (Research). This course is available with permission as an outside option to students on other programmes where regulations permit.
Pre-requisites
Students must have completed Further Mathematical Methods (MA212) and Probability, Distribution Theory and Inference (ST202).
Course content
An introduction to the theory and application of modern multivariate methods used in the Social Sciences: Multivariate normal distribution, principal components analysis, factor analysis, latent variable models, latent class analysis and structural equations models.
Teaching
This course will be delivered through a combination of classes and lectures totalling a minimum of 28 hours across Lent Term. This year, some or all of this teaching may be delivered through a combination of virtual classes and flipped-lectures delivered as short online videos. This course includes a reading week in Week 6 of Lent Term.
Formative coursework
Coursework assigned fortnightly and returned to students via Moodle with comments/feedback before the computer workshops.
Indicative reading
D J Bartholomew, F Steele, I Moustaki & J Galbraith, Analysis of Multivariate Social Science Data (2nd edition);
D J Bartholomew, M Knott & I Moustaki, Latent Variable Models and Factor Analysis: a unified approach;
C Chatfield & A J Collins, Introduction to Multivariate Analysis;
B S Everitt & G Dunn, Applied Multivariate Data Analysis;
K.V. Mardia, J.T. Kent and J.M. Bibby, Multivariate Analysis.
Assessment
Exam (100%, duration: 2 hours) in the summer exam period.
Student performance results
(2016/17 - 2018/19 combined)
| Classification | % of students |
|---|---|
| Distinction | 32.3 |
| Merit | 14.5 |
| Pass | 32.3 |
| Fail | 21 |
Important information in response to COVID-19
Please note that during 2020/21 academic year some variation to teaching and learning activities may be required to respond to changes in public health advice and/or to account for the situation of students in attendance on campus and those studying online during the early part of the academic year. For assessment, this may involve changes to mode of delivery and/or the format or weighting of assessments. Changes will only be made if required and students will be notified about any changes to teaching or assessment plans at the earliest opportunity.
Key facts
Department: Statistics
Total students 2019/20: 7
Average class size 2019/20: 6
Controlled access 2019/20: No
Value: Half Unit
Personal development skills
- Problem solving
- Application of numeracy skills
- Specialist skills
