Academic Year 2021/22, Semester 2
Department of Mathematics, The University of Manchester

The course starts 7th February 2021 and runs for 11 weeks, plus one revision week. There is a three week term break (4 April to 22 April 2021).

Teaching staff:

Wearing a face mask is mandatory (not optional) when attending MATH20802 unless you have an exemption issued by the UoM Occupational Health Service. Please read and follow the COVID-19 safety guidelines to help maintain a safe learning and study environment on campus!

Expectations:

  1. Questions and feedback: This is a course with 400 students. Any questions you may have about the content of the module must be asked in person in the live sessions (5 tutorials). Due to the sheer size of the class tuition by email is not practical.
  2. Example sheets and learning plan: It is important that you do not fall behind with learning. Follow closely the weekly learning plan, read and study all recommended materials and prepare questions in advance to be answered by in the tutorials. Try to solve the exercises every week by yourself or in a study group.
  3. Review lectures, not traditional lectures: The course follows the principle of "flipped learning". This means that the lectures on Monday afternoon are not traditional lectures but have the function to highlight the key aspects of the material that you are expected to have studied beforehand! Hence, studying the lecture notes and the other provided materials is essential.

Overview and syllabus:

The MATH20802 module is an introductory course in statistical methods for second year mathematics students. It is designed to run over the course of 11 weeks and has four parts:

  1. Revisiting essentials (W1)
  2. Likelihood estimation and likelihood ratio tests (W2–W5)
  3. Bayesian learning and inference (W6–W8)
  4. Linear regression models (W9–W11)

This module focuses on conceptual understanding and methods, not on theory, As such, 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).

Flipped classroom:

The course is taught based on the principle of "flipped learning":

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.

To help you understand the lecture notes view the associated lecture videos online:

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

Dates and location:

The live sessions take place on campus at the following dates and locations:

Session Instructor Location Day Time Semester 2 Week
Review lecture K. Strimmer Simon TH E Monday 4pm 1-9, 11-12
Review lecture K. Strimmer Recorded video - Blackboard Monday (2 May 2022) 4pm 10
Tutorial TUT/1 K. Strimmer, K. Siroki Alan Turing_G.207 Tuesday 9am 2-5, 7-12
Tutorial TUT/2 Y. K. Chung, K. Siroki Engineering Building B_2B.025 Tuesday 12noon 2-5, 7-12
Tutorial TUT/3 Y. K. Chung, H. Li Uni Place_1.218 Thursday 3pm 2-5, 7-12
Tutorial TUT/4 Y. K. Chung, S. Li Ellen Wilkinson_C5.1 Thursday 10am 2-5, 7-12
Tutorial TUT/5 Y. K. Chung, S. Y. Kwong Engineering Building B_2B.026 Thursday 12noon 2-5, 7-8
Tutorial TUT/5 Y. K. Chung, S. Y. Kwong Engineering Building B_2B.026 Wednesday 5pm 9-12

Recordings of the review lectures are available as automated podcast on the UoM video portal. The tutorial sessions are not recorded.

Assessment:

There is one in-semester assessment worth 20%. This is an online midterm test.

The end-of-semester assessment is worth the remaining 80%. This is an exam taking place on campus.

Assessment Date Semester 2 Week
Midterm test (20%): From 14 March 2022, 11am (GMT) until 15 March 2022, 11am (GMT) - online test on Blackboard Week 6
Exam (80%): 10th June 2022, 2pm-4pm, Sugden Sports Centre Exam period

Details about the midterm test will be made available on Blackboard. The main exam will be partially open book, i.e. you can bring one sheet of A4 paper with your own notes written on it (both sides).

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 MATH20802 FAQ whether your question has already been asked and answered before!

COVID-19 safety guidelines:

Wearing a face mask is mandatory (not optional) when attending MATH20802! This is a very large class, with no possibility for distancing in a crowded lecture hall. Among the 400 students in this class there will inevitably be many with weak health (e.g. cancer, immunocompromised students due to medication, with weak response to vaccination etc.). It is those vulnerable students we need to protect by mask wearing. Therefore, unless you have an exemption issued by the UoM Occupational Health Service you must wear a mask in the lecture hall and the other teaching spaces!

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.

  1. 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.
  2. 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:
  3. 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!
  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.