Academic Year 2021/22, Semester 1
Department of Mathematics, The University of Manchester
Teaching staff:
Lecturer: Korbinian Strimmer
Office hour: Tuesday, 11am. Please send
email
for an appointment.
Tutors: Ioanna Nikolopoulou (online support), Konstantin Siroki (on campus).
Please read and follow the COVID-19 safety guidelines to help maintain a safe learning and study environment on campus!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:
- Multivariate random variables and estimation in large and small sample settings (W1 and W2)
- Transformations and dimension reduction (W3 and W4)
- Unsupervised learning/clustering (W5 and W7)
- Supervised learning/classification (W8 and W9)
- Measuring and modelling multivariate dependencies (W10)
- 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":
- First, guided by the weekly learning plan the material is studied asynchroneously from lecture notes and lecture videos and by attempting questions and problems on the corresponding worksheets.
- Subsequently, in synchroneous live review sessions the new material of each week is recapitulated and in live tutorials the tasks given the worksheets are discussed in an interactive fashion.
The live teaching sessions take place on campus and also simultaneously broadcasted via Zoom (access details are published on Blackboard).
All sessions will be recorded automatically and corresponding podcasts will appear on the UoM video portal within 24 hours of the event ending.
Course materials:
See also the MATH38161 UoM library reading listTo 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:
- MATH38161 lecture videos: YouTube playlist / UoM video portal
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 |
Assessment:
There is one in-semester take-home assessment worth 20%. This is 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. This exam will take place on campus in Manchester 21 January 2022.
| 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%): | Friday 21 January 2022 | Exam period |
The instructions for the in-semester project will be made available on Blackboard on Monday 15 November, 12 noon . 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!
COVID-19 safety guidelines:
We have a collective responsibility to follow safety measures and advice to reduce the risk to ourselves and others. Below are some measures that we can take to play our part - see also the welcome information on health, well-being and safety.
- Staff and students attending campus are encouraged to carry out lateral flow tests twice a week, and to get vaccinated. Check the details of walk-in vaccination clinics on campus and where to collect free rapid lateral flow testing kits on campus.
- If you have symptoms or have contact with someone who tests positive, you must NOT come to campus. Please follow the guidance on testing, self-isolation, and reporting below:
- University advice on testing
- University advice for self-isolating students
- If you test positive for Covid-19 or if you are isolating/quarantining but have no positive test please use this form to report to the University.
- Please wash or sanitise your hands regularly. Hand sanitising points can be found at various points throughout University buildings -- please look out for these and use them!
- It is expected that face coverings will be worn in lecture theatres and teaching spaces. Unless you are exempt, when on campus please wear a face covering when moving around indoors and attending classes. Face coverings will be available at the main entrances of all campus buildings. I will be wearing a face covering in class, and encourage each of you to do the same unless you are exempt.
- Help reduce crowding and keep buildings flowing safely by:
- arriving to the lecture theatre/classroom no earlier than 5 minutes before the start time, and
- departing the lecture theatre/classroom no later than 10 minutes before start of the next session.
