Academic Year 2022/23, Semester 2
Department of Mathematics, The University of Manchester

The course starts on the 30th January 2023 and runs for 11 weeks, plus one revision week. There is a three week term break (27 March to 14 April 2023).

Teaching staff:

Please read and follow the COVID-19 safety guidelines to help maintain a safe learning and study environment on campus!

Overview and syllabus:

The MATH20802 module is an introductory course in statistical methods 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. This module focuses on conceptual understanding and also provides examples in R.

It is designed to run over the course of 11 weeks and has three parts:

  1. Likelihood estimation and inference (W1–W4)
  2. Bayesian learning and inference (W5–W8)
  3. Linear regression models (W9–W11)

The presentation in this course is non-technical. 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).

Course materials:

See also the MATH20802 UoM library reading list

To get started, download the lecture notes:

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

Further information such as about the midterm test, previous exam papers, feedback to students etc. is available on Blackboard.

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 Y. K. Chung (W1-W6) and K. Strimmer (W7-W10) Simon Theatre B Monday 10:00 W1-W10
Lecture 2 Y. K. Chung (W1-W6) and K. Strimmer (W7-W12) Engineering A Theatre B (2A.041) Tuesday 13:00 W1-W5, W7-W12

There are no lectures on the two bank holiday Mondays (1 May 2023 and 8 May 2023). All lectures are recorded automatically and are available on the UoM video portal.

Session Instructor Location Day Time Semester 2 Week
Tutorial TUT/1 S. Nadarajah Alan Turing G207 Monday 11:00 W1-W5, W7-W10
Tutorial TUT/1 S. Nadarajah Engineering B 2B.025 Friday 16:00 W11-W12
Tutorial TUT/2 Y. K. Chung Alan Turing G205 Monday 11:00 W1-W5, W7-W10
Tutorial TUT/2 Y. K. Chung Alan Turing G205 Friday 16:00 W11-W12
Tutorial TUT/3 Y. K. Chung Engineering B 2B.003 Tuesday 14:00 W1-W5, W7-W12
Tutorial TUT/4 C. Charalambous Engineering B 2B.002 Tuesday 14:00 W1-W5, W7-W12
Tutorial TUT/5 K. Strimmer Samuel Alexander A201 Tuesday 14:00 W1-W5, W7-W12

Note that in semester 2 weeks 11 and 12 the Monday tutorial groups are rescheduled to Friday (due to the bank holidays). The tutorial sessions are not recorded.

Assessment:

The in-semester assessment (midterm test) is worth 20% and is taken on campus in a computer lab. The end-of-semester assessment (written exam) is worth the remaining 80% and is taken on campus.

Assessment Date Semester 2 Week
Midterm test (20%): Tuesday 7 March 2023, 16:00-17:00, various computer labs, see below W6
Exam (80%): Monday 5 June 2023, 9:45-11:45, Armitage Centre (main hall)

The main exam will be "closed book", i.e. you are not allowed to bring any notes to the exam.

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

Session Instructor Location Day Time Semester 2 Week
Midterm test LAB/1 Y. K. Chung Engineering A 2A.021+2A.024 Computer Cluster 4+5 Tuesday 16:00 W6
Midterm test LAB/2 K. Strimmer Engineering A 1A.011 Computer Cluster 1 Tuesday 16:00 W6
Midterm test LAB/3 S. Nadarajah Engineering A 1A.016 Computer Cluster 2 Tuesday 16:00 W6

Teaching format and expectations:

  1. Traditional lecture format: In the academic year 2022/23 this course is taught in traditional format with 2 lectures and 1 tutorial per week. There is no need to watch any videos before coming to the lectures, and you also don't need to study the content before attending the lectures. However, it is essential to study the material of each week within the week before the next lectures and also to solve the corresponding example sheet so that you don't fall behind and continue to be able to follow the subsequent lectures.
  2. Reference text and learning plan: The main reference in this course are the MATH20802 lecture notes. 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.
  3. Example sheets: You are expected to attempt the problems within the week before the tutorials. This will allow you to prepare questions in advance to be answered in the tutorials by the tutors. You are welcome to work together in a group to solve the questions on the worksheet.
  4. Asking questions: In the weekly tutorials we are more than happy to answer in person any questions you may have about the content of the module. The weekly office hours of the lecturers are offered to help with issues that cannot be discussed in public. Due to the size of the class (350 students) individual tuition by email is not possible. Therefore, if you have any questions and would like to get them answered the best way is to attend the tutorials.
  5. Student-led study groups: In addition to the tutorials we encourage students to meet and study together in small study groups. If you would like to set up your own study group please let us know and we will get you in touch with other interested students.

Frequently asked questions and comments:

I hope you enjoy the course! If you have any questions, comments, or corrections please contact the lecturers. First check the MATH20802 FAQ whether your question has already been asked and answered before!

COVID-19 safety guidelines:

We have a collective responsibility to to reduce the risk of COVID-19 and other respiratory viruses to ourselves and others. Below are some measures that we can take to play our part - see also the University info page on "Coronavirus: Frequently asked questions".

  1. We strongly advise anyone who has COVID symptoms or tests positive to stay at home and to avoid contact with other people until your symptoms clear and you no longer test positive using a rapid lateral flow test. Please check the current NHS guidance for further details.
  2. We encourage everyone (if possible) to get vaccinated with an approved COVID-19 vaccine, and to keep vaccinations current.
  3. Wearing a face covering is highly recommended when there are a lot of respiratory viruses circulating and you are in close contact with other people in crowded and enclosed spaces (such as lecture theatres and teaching spaces). Face masks are provided for free at main building entrances.
  4. 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.