Academic Year 2020/21, Term 1
Department of Mathematics, The University of Manchester

The course starts 5th October 2020 and runs for 11 weeks (with no break). One tutorial group is online, the other one is mixed both on campus and online.

Teaching staff:

Lecturer: Korbinian Strimmer
Office hour: Monday, 2pm. Please send email for an online appointment.

Overview and syllabus:

The MATH38161 module is an introductory course in Multivariate Statistics and Machine Learning for third year mathematics students. It is designed to run over the course of 11 weeks in six parts, each covering a particular aspect of multivariate statistics and machine learning:
  1. Multivariate random variables and estimation in large and small sample settings (W1 and W2)
  2. Transformations and dimension reduction (W3 and W4)
  3. Unsupervised learning/clustering (W5 and W6)
  4. Supervised learning/classification (W7 and W8)
  5. Measuring and modelling multivariate dependencies (W9)
  6. Nonlinear and nonparametric models (W10, W11)

The presentation of the material focuses on concepts and methods. In the worksheets the practical implementation and application in R of the methods is explored.

Flipped classroom:

The course is taught based on the principle of "flipped learning":

Course materials:

See also the MATH38161 UoM library reading list To get started, download the learning plan, the lecture notes and worksheets: To help you understand the lecture notes view the associated lecture videos online: Further information such as coursework instructions, previous exam papers, feedback to students etc. is available on Blackboard.

Dates and location:

The synchronous live sessions take place at the following dates and locations:

Session Location Day Time Semester 1 Week
Review lecture Online - Blackboard Monday 13:00 1-11
Tutorial group 1 Online - Blackboard Tuesday 10:00 1-6, 10-11
Uni Place TH B Tuesday 10:00 7-9
Tutorial group 2 Online - Zoom Thursday 10:00 1-11

Two online sessions (review lecture, Tuesday tutorial) are delivered via Blackboard using Blackboard Collaborate Ultra. If you have trouble accessing the online course room on Blackboard please check that your browser is supported by Blackboard and that it is a recent version (recommended browser on desktop: Firefox ESR).

The third online session (Thursday tutorial) is delivered via Zoom. The corresponding meeting ID and password is shown on Blackboard.

Recordings of the review lectures are available on Blackboard. The tutorial sessions are not recorded.


There is one in-semester assessment worth 20%. This is a small project requiring data analysis in R and writing of a corresponding statistical report, preferably in R Markdown. The end-of-semester assessment is worth the remaining 80% and is concerned with theory and methods. It will be a 100% take home exam.

Assessment Date Semester 1 Week
Project work (20%): Announced: Monday 23 November 2020, 12 noon
Submission: Monday 7 December 2020, 12 noon
8 and 10
Exam (80%): January 2021, tba Exam period

The instructions for the in-semester project will be made available on Blackboard two weeks before the due deadline. The expected amount of time to complete the project is 10h.

Frequently asked questions and comments:

I hope you enjoy the course. If you have any questions, comments, or corrections please contact the lecturer. First check the MATH38161 FAQ whether your question has already been asked and answered before!