Academic Year 2021/22, Semester 1
Department of Mathematics, The University of Manchester

The course starts 28th September 2021 and runs in semester weeks W1-W5 and W7-W12. There is no teaching in W6.

Teaching staff:

Lecturer: Korbinian Strimmer
Office hour: Tuesday, 11am. Please send email for an 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 W7)
  4. Supervised learning/classification (W8 and W9)
  5. Measuring and modelling multivariate dependencies (W10)
  6. Nonlinear and nonparametric models (W11, W12)

The presentation of the material focuses on concepts and methods. In the worksheets the practical implementation and application in R 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 lecture notes:

In addition, download the weekly learning plan and worksheets with solutions from Blackboard.

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 ATB G.209 Tuesday 10:00 W1-W5, W7-W12
Tutorial ATB G.209 Thursday 16:00 W1-W5, W7-W12

The live teaching sessions take place on campus but will be 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 15 November 2021, 12 noon
Submission: Monday 6 December 2021, 12 noon
Work on project in W8, W9 and W10
Exam (80%): January 2022 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!