Academic Year 2024/25, Semester 2
Department of Mathematics, The University of Manchester
Teaching staff:
Lecturer: Korbinian Strimmer
Office hour: Thursday, 11am. Please send
email
for an appointment.
Academic tutorial leads: I. Henriques-Cadby, L. Pellis, Y. K. Chung, K. Strimmer
Overview and syllabus:
The MATH27720 Statistics 2 module is an introductory course in likelihood and Bayes inference for second year mathematics students. In this module you will learn about the foundations of statistical learning using likelihood and Bayesian approaches and also how these methods are underpinned by entropy.
The module is designed to run over the course of 10 weeks and has the following structure:
- Entropy and likelihood (W1–W5)
- Bayesian statistics (W6–W10)
The presentation in this course focuses on concepts and methods. The aim is to offer insights how diverse statistical approaches are linked and to demonstrate that statistics offers a concise and coherent theory of information rather than being an adhoc collection of “recipes” for data analysis (a common but wrong perception of statistics).
Teaching Format:
This course is taught in traditional format with 3 contact hours per week, either 3 lectures (odd weeks) or 2 lectures and 1 tutorial (even weeks).
The main reference in this course are the MATH27720 Statistics 2 lecture notes and you are expected to revisit the content of the lectures each week using these notes. The weekly learning plan available on Blackboard indicates which parts of the notes are relevant in each study week. In the biweekly tutorials the problems in worksheets are discussed. You are expected to attempt at least some of the problems before the tutorials. You are welcome to work together in a group to solve the problems. Solutions will be provided after the last tutorial has completed.
The delivery mode of this module follows the traditional lecture format, using the visualiser for presenting the content. It is essential to revisit the material of each week regularly using the your own notes taken during the lectures, as well as the provided official MATH27720 Statistics 2 lecture notes and worksheets, so that you don't fall behind and continue to be able to follow the subsequent lectures.
All lectures (but not the tutorials!) will be recorded automatically and corresponding podcasts will appear on the UoM video portal within 24 hours of each session.
Course materials:
See also the MATH27720 Statistics 2 UoM library reading listTo get started, download the lecture notes:
- MATH27720 Statistics 2 lecture notes (online)
- MATH27720 Statistics 2 lecture notes (PDF in A4 format for printing)
In addition, download the weekly learning plan and the worksheets with solutions from Blackboard. 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 campus at the following dates and locations:
Session | Instructor | Location | Day | Time | Semester 2 Week |
---|---|---|---|---|---|
Lecture 1 | K. Strimmer | University Place Theatre B | Tuesday | 10:00 | W1-W10 |
Lecture 2 | K. Strimmer | Nancy Rothwell Building Theatre A (2A.040) | Tuesday | 14:00 | W1-W6, W8-W10 |
Lecture 3 | K. Strimmer | Nancy Rothwell Building Theatre A (2A.040) | Friday | 9:00 | W1, W3, W5, W7, W9 |
There are no lectures in Week 11 and 12. Instead of the second lecture in Week 7 there is the midterm test. All lectures are recorded automatically and are available on the UoM video portal.
Session | Instructor | Location | Day | Time | Semester 2 Week |
---|---|---|---|---|---|
Tutorial TUT2/2 | I. Henriques-Cadby | Oddfellows Hall_G.010 | Wednesday | 10:00 | W2, W4, W6, W8, W10 |
Tutorial TUT2/6 | L. Pellis | Oddfellows Hall_G.007 | Wednesday | 10:00 | W2, W4, W6, W8, W10 |
Tutorial TUT2/5 | L. Pellis | Oddfellows Hall_G.010 | Wednesday | 11:00 | W2, W4, W6 |
Tutorial TUT2/8 | Y. K. Chung | Roscoe 4.3 | Wednesday | 12:00 | W2, W4, W6, W8, W10 |
Tutorial TUT2/3 | K. Strimmer | Oddfellows Hall_G.010 | Thursday | 9:00 | W2, W4, W6, W8, W10 |
Tutorial TUT2/4 | Y. K. Chung | Oddfellows Hall_G.007 | Thursday | 9:00 | W2, W4, W6, W8, W10 |
Tutorial TUT2/1 | K. Strimmer | Alan Turing G.207 | Thursday | 11:00 | 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 11 March 2025, 15:00-15:50, various computer labs, see below | W7 |
Exam: | tba | Exam Period W3 |
The midterm test will take place in the following computer labs:
Session | Instructor | Location | Day | Time | Semester 2 Week |
---|---|---|---|---|---|
Midterm test/01 | K. Strimmer | Simon 6.004 Comp Cluster | Tuesday | 15:00 | W7 |
Midterm test/02 | M. Bhattacharjee | Nancy Rothwell_1A.033 CompCluster 3 | Tuesday | 15:00 | W7 |
Midterm test/03 | Y. K. Chung | Nancy Rothwell_2A.021 CompCluster 4 | Tuesday | 15:00 | W7 |
Midterm test/04 | G. Peskir | Nancy Rothwell_1A.016 CompCluster 2 | Tuesday | 15:00 | W7 |
Midterm test/05 | S. Nadarajah | Nancy Rothwell_2A.024 CompCluster 5 | Tuesday | 15:00 | W7 |
Midterm test/06 (DASS) | Peter Johnson | Alan Turing G.105 | Tuesday | 15:00 | 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!