MMath Mathematics and Statistics
About this course
MMath in Mathematics and Mathematics and Statistics. Core topics include Programming, Data Analysis, Statistics, Mathematical Modelling, Financial Analysis, Accounting, and Artificial Intelligence & Machine Learning. The programme includes a staff-supervised mathematical project in the final year.
Written by AI from the university's course page and module list. It can get details wrong, so check the official course page before you rely on it.
Entry requirements
A level: A*AA including A* in Mathematics or Further Mathematics A-level. Further Mathematics is preferred but not essential. When the Further Maths A-level is taken it will be included in the offer
What students say
Based on about 46 final-year students who answered, across similar courses at this university
- Teaching on my course: 87%
- Learning opportunities: 84%
- Assessment and feedback: 85%
- Academic support: 94%
- Organisation and management: 87%
- Learning resources: 93%
- Student voice: 83%
Do students stay on the course?
Based on about 15 students who started (a small group: a rough guide only)
- Continued on course: 95%
- Left higher education: 5%
What graduates do next
Based on about 68 graduates who answered, across similar courses at this university
- Working: 64%
- Working and studying: 14%
- Further study: 9%
- Unemployed: 7%
Most common jobs
- Finance Professionals: 19%
- Business, Research and Administrative Professionals: 14%
- Business and public service associate professionals: 12%
- Information Technology Professionals: 12%
- Teaching Professionals: 10%
- Find their work meaningful: 72%
- Feel on track for their future plans: 66%
- Use what they learnt on the course: 46%
Where graduates work (5 years on)
Based on about 290 graduates, across similar courses at this university
- North East: 1%
- North West: 51%
- Yorkshire and the Humber: 6%
- East Midlands: 3%
- West Midlands: 5%
- East of England: 3%
- London: 18%
- South East: 5%
- South West: 4%
- Wales: 2%
- Scotland: 1%
Who gets in
Based on about 15 students who started (a small group: a rough guide only)
- A levels: 95%
- Foundation course: 5%
Accreditation & quality ratings
- This course is accredited by the Institute of Mathematics and its Applications (IMA) and meets the educational requirements for the Chartered Mathematician (CMath) designation. It is also recognised as meeting the educational requirements for IMA membership at the appropriate level, from Student Member to Fellow.
- Accredited by the Royal Statistical Society (RSS) for the purpose of eligibility for Graduate Statistician status.
TEF 2023 (whole university): Silver overall, Silver for student experience, Gold for student outcomes.
Modules
- Linear Algebra
- Real Analysis
- Mathematical Foundations & Analysis
- Mathematical Problem Solving
- Introduction to Vector Calculus
- ODEs and Applications
- Probability I
- Statistics I
- Mathematical Communication and Group Projects
- Practical Statistics
- Linear Regression Models
- Stochastic Processes
- Probability and Statistics 2
- Fundamentals of Financial Reporting B
- Fundamentals of Management Accounting
- Introduction to Corporate Finance and Financial Instruments
- Technology, Strategy and Innovation
- New Product Development and Innovation
- Marketing
- Logic and Modelling
- Introduction to AI
- Teaching and Learning of Mathematics
- Science & the Modern World
- Foundations of finance: Investments and the time and value of money
- Principles of Mathematical Modelling
- Introduction to Financial Mathematics
- Metric Spaces
- Rings & Fields
- Groups and Geometry
- Numerical Analysis 1
- Fluid Mechanics
- Partial Differential Equations & Vector Calculus
- Critical Thinking
- Formal Logic
- Introduction to Corporate Finance and Financial Instruments
- Technology, Strategy and Innovation
- New Product Development and Innovation
- Marketing
- Management of Knowledge and Innovation
- Financial Derivatives
- Financial Engineering
- Logic and Modelling
- Introduction to AI
- Giving Meaning to Programs
- Teaching and Learning of Mathematics
- Theories of Equity in Education
- Educational Leadership
- Independent Study and Technical Explanations
- The Nuclear Age: Global Nuclear Threats from Hiroshima to Today
- Double Project
- Mathematics Education
- Project (Semester One)
- Project (Semester 2)
- Topology and Analysis
- Analysis and Geometry in Affine Space
- Differential Geometry of Curves and Surfaces
- Advanced Algebra
- Coding Theory
- Hyperbolic Geometry
- Algebraic Geometry
- Number Theory
- Combinatorics and Graph Theory
- Mathematical Logic
- Complex Analysis&Applications
- Wave Motion
- Elasticity and Viscous Fluid Dynamics
- Mathematical Biology
- Methods of Applied Mathematics
- Mathematics of a Finite Planet
- Matrix Analysis
- Numerical Analysis 2
- Problem Solving by Computer
- Mathematics and Applications of Machine Learning
- Martingales with Applications to Finance
- Markov Processes
- Foundations of Modern Probability
- Tools for Risk Management
- Time Series Analysis
- Medical Statistics
- Multivariate Statistics and Machine Learning
- Generalised Linear Models
- Mathematical Modelling in Finance
- Mortality Modelling in Insurance
- Stochastic Calculus
- Brownian Motion
- Martingale Theory
- Time Series Analysis and Forecasting
- Multivariate Statistics
- Design and Analysis of Experiments
- Longitudinal and Spatial Data Analysis
- Statistical Theory
- Bayesian Statistics
- Statistical Machine Learning
- Advanced Regression Methods
- Tools and Techniques for Enterprise
- Advanced Technology Enterprise
- Interdisciplinary Sustainable Development
- Formal Logic
- Topology and Analysis
- Analysis and Geometry in Affine Space
- Differential Geometry of Curves and Surfaces
- Advanced Algebra
- Coding Theory
- Hyperbolic Geometry
- Algebraic Geometry
- Number Theory
- Combinatorics and Graph Theory
- Mathematical Logic
- Complex Analysis&Applications
- Wave Motion
- Elasticity and Viscous Fluid Dynamics
- Mathematical Biology
- Methods of Applied Mathematics
- Mathematics of a Finite Planet
- Matrix Analysis
- Numerical Analysis 2
- Problem Solving by Computer
- Mathematics and Applications of Machine Learning
- Martingales with Applications to Finance
- Markov Processes
- Foundations of Modern Probability
- Tools for Risk Management
- Time Series Analysis
- Medical Statistics
- Multivariate Statistics and Machine Learning
- Generalised Linear Models
- Mathematical Modelling in Finance
- Mortality Modelling in Insurance
- Double Project
- Project (Semester 1)
- Project (Semester 2)
- Computational Finance
- Measure Theory and Ergodic Theory
- Differentiable Manifolds
- Algebraic Topology
- Riemann Surfaces
- Lie Algebras
- Galois Theory
- Algebraic Number Theory
- Graph Theory
- Representation Theory
- Computation and Complexity
- Category Theory
- Model Theory
- Dynamical Systems
- Introduction to Uncertainty Quantification
- Advanced Uncertainty Quantification
- Mathematical Methods for PDE's
- Stability Theory
- Continuum Mechanics
- Transport Phenomena and Conservation Laws
- Approximation Theory and Finite Element Analysis
- Numerical Optimisation & Inverse Problems
- Stochastic Calculus
- Brownian Motion
- Martingale Theory
- Time Series Analysis and Forecasting
- Multivariate Statistics
- Design and Analysis of Experiments
- Longitudinal and Spatial Data Analysis
- Statistical Theory
- Bayesian Statistics
- Statistical Machine Learning
- Advanced Regression Methods
- Stochastic Modelling in Finance
- Scientific Computing
Questions about this course
How much do graduates of MMath Mathematics and Statistics at University of Manchester earn?
The median salary is £31,000 after 15 months, £31,000 after 3 years, £42,000 after 5 years. After five years the middle half of graduates earn between £31,000 and £55,500. The £42,000 median after five years is £2,500 more than the UK median for Mathematics.
What do graduates of MMath Mathematics and Statistics at University of Manchester do next?
87% were in work or further study 15 months after finishing (Graduate Outcomes 2023-24).
Are students happy with the teaching on MMath Mathematics and Statistics at University of Manchester?
87% of final-year students were positive about the teaching in the National Student Survey 2025-26.
What grades do I need for MMath Mathematics and Statistics at University of Manchester?
The typical offer is A*AA at A level. The average entrant had 162 UCAS points.
Is MMath Mathematics and Statistics at University of Manchester accredited?
Yes. This course is accredited by the Institute of Mathematics and its Applications (IMA) and meets the educational requirements for the Chartered Mathematician (CMath) designation. It is also recognised as meeting the educational requirements for IMA membership at the appropriate level, from Student Member to Fellow. Accredited by the Royal Statistical Society (RSS) for the purpose of eligibility for Graduate Statistician status.
Does MMath Mathematics and Statistics at University of Manchester include a placement year or year abroad?
The course has an optional placement year.
How many students continue on MMath Mathematics and Statistics at University of Manchester?
95% of students continued into their second year, and 5% left higher education.