ST405      Half Unit
Multivariate Methods

This information is for the 2021/22 session.

Teacher responsible

Dr Yunxiao Chen


This course is available on the MPhil/PhD in Statistics, MSc in Data Science, MSc in Health Data Science, MSc in Marketing, MSc in Statistics, MSc in Statistics (Financial Statistics), MSc in Statistics (Financial Statistics) (LSE 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.


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.


This course will be delivered through a combination of computer workshops, lectures, and Q&A sessions, totalling a minimum of 28 hours across Lent Term. This year, some of this teaching may be delivered through a combination of computer workshops 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.


Exam (100%, duration: 2 hours) in the summer exam period.

Course selection videos

Some departments have produced short videos to introduce their courses. Please refer to the course selection videos index page for further information.

Student performance results

(2017/18 - 2019/20 combined)

Classification % of students
Distinction 43.1
Merit 11.8
Pass 27.5
Fail 17.6

Important information in response to COVID-19

Please note that during 2021/22 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 differing needs of students in attendance on campus and those who might be studying online. For example, this may involve changes to the mode of teaching 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 2020/21: 15

Average class size 2020/21: 7

Controlled access 2020/21: Yes

Value: Half Unit

Guidelines for interpreting course guide information

Personal development skills

  • Problem solving
  • Application of numeracy skills
  • Specialist skills