Academic Year 2025/26, Semester 2
Department of Mathematics, The University of Manchester

The course starts on 2th February 2026, runs for 10 weeks and ends on 1 May 2026. The term break is between Week 8 and Week 9 (from 30 March to 17 April 2025).

Teaching staff:

Lecturer: Korbinian Strimmer
Office hour: Thursday 2pm. Please send email for an appointment.

Academic tutorial leads: Y.-K Chung, P. Foster, K. Strimmer.

Overview and syllabus:

The MATH27720 Statistics 2 module is an introductory course in likelihood and Bayes inference intended for second-year mathematics and computer science students. In this course you'll study the foundations of statistical learning using both likelihood and Bayesian approaches with focus on conceptual understanding.

The module is designed to run over the course of 10 weeks and has the following structure:

  1. Models, information and likelihood (W1–W5)
  2. Bayesian statistics (W6–W10)

The first part of the module (Weeks 1–5) explores the method of maximum likelihood drawing on relevant aspects of information theory with application to standard models such as exponential families. The second part of this module (Weeks 6–10) focuses on the Bayesian approach to statistical estimation and inference, presented as a natural extension of likelihood-based methods that addresses some limitations of maximum likelihood.

Teaching Format:

This course is fully in person with 3 contact hours per week over 10 weeks - either 3 lectures (odd weeks) or 2 lectures and 1 tutorial (even weeks). The lectures take place on Tuesday, Thursday and Friday, and tutorials on Thursday and Friday. Check your personal timetable for details.

This module is delivered traditionally, using a visualiser to present content. You should take your own notes during lectures.

The primary reference for this course (Semester 2) are the MATH27720 Statistics 2 lecture notes. You should review the lecture material weekly using these notes. The weekly learning plan on Canvas indicates which section of the notes are relevant for each study week.

In biweekly tutorials we discuss the worksheet problems. You should attempt the problems beforehand, and group work is encouraged. Solutions are posted after the final tutorial each week.

All lectures (tutorials excluded) are recorded automatically, and podcast versions will appear on the UoM video portal within 24 hours of each session.

Course materials:

See also the MATH27720 UoM library reading list

To get started, download the lecture notes:

In addition, download the weekly learning plan and the worksheets with solutions from Canvas. There you can also find instructions for the midterm test and previous exam papers.

Furthermore, the following supplementary notes will be useful:

These are also available in PDF format for A4 printing.

Dates and location:

The lectures take place on the following dates and at the following locations:

Session Instructor Location Day Time Semester 2 Week
Lecture3 K. Strimmer Crawford House_TH 1 Tuesday 16:00 W1-W10
Lecture5 K. Strimmer Crawford House_TH 1 Thursday 16:00 W1, W3, W5, W9
Lecture5 K. Strimmer Simon_TH E Friday 10:00 W1-W10

There are no lectures in Week 11 and 12. Instead of the one of the lectures in Week 7 there is the midterm test. All lectures are recorded automatically and are available on the UoM video portal.

The tutorials take place on the following dates and at the following locations:

Session Instructor Location Day Time Semester 2 Week
Tutorial2/06 K. Strimmer James Chadwick 3.009 Thursday 13:00 W2, W4, W6, W8, W10
Tutorial2/07 K. Strimmer Uni Place 2.218 Friday 11:00 W2, W4, W6, W8, W10
Tutorial2/03 P. Foster Roscoe 2.4 Friday 14:00 W2, W4, W6, W8, W10
Tutorial2/02 K. Strimmer Roscoe 1.007 Friday 15:00 W2, W4, W6, W8, W10
Tutorial2/01 Y.-K. Chung Uni Place 4.204 Friday 15:00 W2, W4, W6, W8, W10
Tutorial2/04 K. Strimmer Uni Place 4.204 Friday 16:00 W2, W4, W6, W8, W10
Tutorial2/05 P. Foster Roscoe 1.007 Friday 16:00 W2, W4, W6, W8, W10

There are no tutorials in Week 12. Tutorials are not recorded. If you have any questions about the content of the course then attending the tutorials is your best opportunity to get those questions answered in person.

Assessment:

The in-semester assessment for Statistics 2 (midterm test) is worth 10% of the overall mark for MATH27720 and is taken on campus in a computer lab. The end-of-semester assessment for Statistics 2 (half of the written MATH27720 exam) is worth 40% and is taken on campus.

Note that Semester 1 (Probability 2) and Semester 2 (Statistics 2) each contribute 50% of the total available marks for MATH27720. Half of the written exam will be about Statistics 2 and the other half about Probability 2.

Assessment Date Semester 2 Week
Statistics 2 midterm test: Tuesday 17 March 2026, 1pm-2pm, various computer labs on campus, see below W7
Exam: tbd Exam Period tbd

The midterm test will take place in the following computer labs:

Session Instructor Location Day Time Semester 2 Week
TEST2/01 K. Strimmer Chem. Comp. Cluster 17 March 2026 1pm W7
TEST2/02 J. Yuan Alan Turing G.105+G1.05A 17 March 2026 1pm W7
TEST2/03 J. Ferns Nany Rothwell 1A.011 Comp. Cluster 1 17 March 2026 1pm W7
TEST2/04 D. Denisov Nancy Rothwell 1A.016 Comp. Cluster 2 17 March 2026 1pm W7
TEST2/05 P. Foster Nancy Rothwell 1A.033 Comp. Cluster 3 17 March 2026 1pm W7
TEST2/DASS R. Gaunt Schuster 1.015 17 March 2026 1pm W7

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 MATH27720 Statistics 2 FAQ whether your question has already been asked and answered before!