- UCAS course code
- G101
- UCAS institution code
- M20
Bachelor of Science (BSc)
BSc Mathematics with Placement Year
Duration: 4 years
Year of entry: 2025
UCAS course code: G101 / Institution code: M20
- Key features:
Industrial experience
Accredited course
- Typical A-level offer: A*AA including specific subjects
- Typical contextual A-level offer: A*AB including specific subjects
- Refugee/care-experienced offer: A*BB including specific subjects
- Typical International Baccalaureate offer: 37 points overall with 7,6,6 at HL, including specific requirements
Fees and funding
Fees
Tuition fees for home students commencing their studies in September 2025 will be £9,535 per annum (subject to Parliamentary approval). Tuition fees for international students will be £34,500 per annum. For general information please see the undergraduate finance pages.
Policy on additional costs
All students should normally be able to complete their programme of study without incurring additional study costs over and above the tuition fee for that programme. Any unavoidable additional compulsory costs totalling more than 1% of the annual home undergraduate fee per annum, regardless of whether the programme in question is undergraduate or postgraduate taught, will be made clear to you at the point of application. Further information can be found in the University's Policy on additional costs incurred by students on undergraduate and postgraduate taught programmes (PDF document, 91KB).
Course unit details:
Probability I
| Unit code | MATH11711 |
|---|---|
| Credit rating | 10 |
| Unit level | Level 1 |
| Teaching period(s) | Semester 1 |
| Available as a free choice unit? | No |
Overview
This unit introduces the basic ideas and techniques of probability, including the handling of random variables and standard probability distributions and the crucial notions of conditional probability and of independence, to equip the students with the necessary knowledge required for probability related courses in their later studies
Aims
The unit aims to introduce the basic ideas and techniques of probability, including the handing of random variables and standard probability distributions and the crucial notions of conditional probability and of independence, to equip the students with the necessary knowledge required for probability related courses in their later studies.
Learning outcomes
On the successful completion of the course, students will be able to:
1. describe how mathematics models randomness and model real-world situations involving randomness
2. compute probabilities and expectations using various formulas and demonstrate why those formulas hold
3. describe standard distributions and apply them in the context of a sequence of biased coin flips, exponential waiting times, or the sum of independent random variables
4. explain and appraise statements that hold for a large class of distributions like the Central Limit Theorem, or the law of large numbers
Syllabus
The course gives a general introduction to probability theory and is a prerequisite for all future probability and statistics courses.
1. Probability space: sample space and counting principles; events and probability.
2. Conditional probability and independence.
3. Discrete and continuous random variables; (joint) distributions.
4. Expectation and variance of a random variable.
5. Classical distributions including the Binomial, Geometric, Poisson, Normal and Exponential distributions.
6. Probability theory: The Central Limit Theorem. Law of Large Numbers.
Assessment methods
| Method | Weight |
|---|---|
| Other | 10% |
| Written exam | 90% |
Feedback methods
There are supervisions in alternate weeks which provide an opportunity for students' work to be marked and discussed and to provide feedback on their understanding. Coursework or in-class tests (where applicable) also provide an opportunity for students to receive feedback. Students can also get feedback on their understanding directly from the lecturer, for example during the lecturer's office hour
Recommended reading
1) S. Ross, A First Course in Probability, Macmillan.
2) D. Stirzaker, Elementary Probability, Cambridge University Press. Available electronically through the library.
3) HELM consortium, HELM Workbooks 35, 37, 38 and 39, Open Access Publication. Available electronically on the internet.
Study hours
| Scheduled activity hours | |
|---|---|
| Lectures | 22 |
| Tutorials | 5 |
| Independent study hours | |
|---|---|
| Independent study | 73 |
Teaching staff
| Staff member | Role |
|---|---|
| Peter Johnson | Unit coordinator |