Bachelor of Science (BSc)
BSc Actuarial Science and Mathematics
Duration: 3 years
Year of entry: 2025
UCAS course code: NG31 / Institution code: M20
- Key features:
Scholarships available
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).
Scholarships/sponsorships
The University of Manchester is committed to attracting and supporting the very best students. We have a focus on nurturing talent and ability and we want to make sure that you have the opportunity to study here, regardless of your financial circumstances.
For information about scholarships and bursaries please visit our undergraduate student finance pages and our Department funding pages .
Course unit details:
Statistics I
| Unit code | MATH11712 |
|---|---|
| Credit rating | 10 |
| Unit level | Level 1 |
| Teaching period(s) | Semester 2 |
| Available as a free choice unit? | No |
Overview
The unit introduces students to basic ideas in exploratory data analysis, parametric statistical modelling, inferential statistics, and statistical computing in R, thereby preparing them for further study in Statistics in the second and third year.
Aims
The unit aims to introduce students to basic ideas in exploratory data analysis, parametric statistical modelling, inferential statistics, and statistical computing in R, thereby preparing them for further study in Statistics in the second and third year.
Learning outcomes
On the successful completion of the course, students will be able to:
- define elementary statistical concepts and terminology such as sampling distribution, unbiasedness, confidence intervals and hypothesis tests
- analyse and compare statistical properties of simple estimators and tests
- conduct exploratory data analysis and statistical inferences, including confidence intervals and hypothesis tests, in simple one and two-sample situations
- interpret the results of exploratory data analyses and statistical inferences in simple situations
- use the statistical computing software R to carry out simple data analysis, including presentation of graphical and numerical summaries, and simulation
Assessment methods
| Method | Weight |
|---|---|
| Other | 10% |
| Written exam | 80% |
| Report | 10% |
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
G M Clarke and D Cooke, A Basic Course in Statistics (Fourth Edition) Oxford University Press, 1998;
Robert V Hogg, Introduction to Mathematical Statistics (Sixth Edition) Prentice Hall, 2005;
Sheldon M Ross, Introduction to Probability and Statistics for Engineers and Scientists (Third edition) Elsevier Science, 2004;
Michael J Crawley, Statistics: An Introduction Using R. John Wiley & Sons Ltd, 2000
Study hours
| Scheduled activity hours | |
|---|---|
| Lectures | 12 |
| Tutorials | 12 |
| Independent study hours | |
|---|---|
| Independent study | 76 |
Teaching staff
| Staff member | Role |
|---|---|
| Lorenzo Pellis | Unit coordinator |
| Ian Hall | Unit coordinator |