- UCAS Code: G100
- Accreditation: Institute of Mathematics & its Applications
Part-time study: available
Study with us
- understand how mathematics is applied to solve practical problems
- learn how to use statistics to explore and try to explain the uncertain world in which we live
- accredited by the Institute of Mathematics and its Applications and the Royal Statistical Society
- flexibility to transfer between MMath and BSc Honours
- by taking half of your final two years’ classes in statistics, you can graduate with the degree title of Mathematics & Statistics
Why this course?
Mathematics is everywhere: weather forecasting, cash machines, secure websites, electronic games, liquid crystal displays and statistical data analysis.
Statistics is the area of mathematics we use to explore and try to explain the uncertain world in which we live. You’ll be familiar with the use of statistics in opinion polls and market research. It is also central to the manufacture and testing of many products, and, in particular, showing that modern drugs are effective and safe.
Our flexible degree structure enables transfer between courses with the opportunity to study abroad.
What you’ll study
The BSc (Honours) degree is a four-year programme. Each year contains compulsory classes and some years contain either optional classes, which relate to different areas of mathematics and/or elective classes from other subject areas in the University.
Years 1 & 2
In addition to core mathematical methods, you’ll study applied analysis, mechanics, numerical analysis and statistics. You also choose elective classes.
Years 3 & 4
You’ll choose from a range of Mathematics & Statistics classes from one or more of the specialist application areas.
As part of the final Honours year, you will undertake a project that includes a written report and an oral presentation.
Topics offered in Honours-year classes include the mathematics of financial derivatives, mathematical modelling in biology and medicine, numerical analysis, and the mathematics of networks.
Mathematics & Statistics
If you take half of your 3rd and 4th year classes in Statistics you can graduate with the degree title of BSc (Honours) in Mathematics & Statistics.
You have the opportunity to spend time studying abroad, normally in the third year of the course. We have links with three universities in Europe for exchanges under the European Union's SOCRATES (ERASMUS) scheme.
You can study at:
- University of Limerick, Republic of Ireland
- Johannes Kepler University, Linz, Austria
- Technical University of Denmark, Lyngby, Denmark
We also have links with several non-European universities, and our students have recently studied abroad at:
- Nanyang Technological University, Singapore
- University of Otago, New Zealand
- University of Toronto, Canada
Accredited by the Institute of Mathematics and its Applications for the purpose of meeting in full the educational requirement for chartered status.
My favourite thing about Glasgow is the friendly atmosphere and how welcoming everyone is.
Introduction to Calculus
Applications of Calculus
The fundamental concepts of calculus (differentiation and integration) presented in Applications of Calculus will be examined in more detail, extended to a larger class of functions by means of more sophisticated methods, including an introduction to complex numbers and variables, all demonstrated in application to practical problems including solving basic first and second-order differential equations.
Geometry & Algebra with Applications
This class will introduce you to vectors and matrices, along with the idea of mathematical modelling through their application to real-world problems.
Statistics & Data Presentation
Some basic ideas and techniques of statistics will be presented while introducing some essential study skills, allowing you to develop and practice personal and technical skills eg self-study, teamwork, analysing data, writing reports and making presentations.
Applying Mathematics 1
To introduce students to some elementary number theory with interesting modern applications. Codes and encryption: problem description and motivation. Mathematical background: natural numbers and integers, factorisation, proof by induction, highest common factor, lowest common multiple, Euclidean Algorithm, prime numbers and the Fundamental Theorem of Arithmetic, Diophantine equations, modular arithmetic, congruence mod n, solving equations in Zn, Euler's phi-function and theorem. Applications to International Standard Book Numbers, Universal Product Codes, affine and exponential ciphers, and the RSA cryptosystem.
Applying Mathematics 2
To introduce students to areas of mathematics (graph theory) not usually met in school or college courses. Graph theory: Problem description and motivation (e.g. Konigsberg Bridge, three utilities problem, the travelling salesman problem). Graphs, multigraphs, isomorphic graphs, sub-graphs, paths, trails, circuits and cycles, Eulerian and Hamiltonian graphs, weighted graphs, minimal spanning trees, critical path analysis, planar graphs, Euler’s formula, Colouring of Graphs, Digraphs, Network Flows, and Social Network Analysis. Brief introduction to network science.
Linear Algebra & Differential Equations
This class will introduce you to the basic ideas of linear algebra, such as matrices and determinants, vector spaces, bases, eigenvalues and eigenvectors. You'll study various standard methods for solving ordinary differential equations and understand their relevance.
Basic ideas, techniques and results for calculus of two and three variables, along with differentiation and integration over curves, surfaces and volumes of both scalar and vector fields will be presented.
This class will give a rigorous treatment of convergence of sequences and infinite series of real numbers and of continuity, differentiability and integrability of functions of a real variable, and will illustrate the importance of these concepts in the analysis of problems arising in applications.
Probability & Statistical Inference
Presentation of the basic concepts of probability theory and statistical inference will be covered to provide you with the tools to appropriately analyse a given data set and effectively communicate the results of such analysis.
Introduction to Newtonian Mechanics
This class will develop your appreciation of the basic concepts of force, momentum and energy, and of Newton’s laws of motion and will equip you to apply these concepts to model physical systems, in particular the orbital motion of bodies.
Mathematical & Statistical Computing
This class will introduce you to the R computing environment. It'll enable you to use R to import data and perform statistical tests, allow you to understand the concept of an algorithm and what makes a good algorithm and will equip you for implementing simple algorithms in R.
Complex Variables & Integral Transforms
This class will introduce functions of a complex variable, define concepts such as continuity, differentiability, analyticity, line integration, singular points, etc. It'll examine some important properties of such functions, and consider some applications of them, eg conformal mappings, and the evaluation of real integrals using the Residue Theorem. It'll also introduce you to Fourier and Laplace transform methods for solving linear ordinary differential equations and convolution type integral equations.
Here we'll introduce basic algebraic structures, with particular emphasis on those pertaining to finite dimensional linear spaces and deepen your understanding of linear mappings. We'll also provide an introduction to inner product spaces and bilinear forms.
We'll introduce you to analytical methods for solving ordinary and partial differential equations so you'll develop an understanding along with technical skills in this area.
Applicable Analysis 2
We'll introduce you to the basic theory and applications of metric spaces, normed vector spaces and Banach spaces, inner product spaces and Hilbert spaces, and bounded linear operators on normed linear spaces.
Inference & Regression Modelling
This class will:
- review the concepts of probability distributions and how to work with these
- present approaches to parameter estimation, focusing on maximum likelihood estimation, bootstrap estimation, and properties of estimators
- present hypothesis testing procedures, including classical likelihood ratio tests and computer-based methods for testing parameter values, and goodness-of-fit tests.
- introduce and provide understanding of the least squares multiple regression model, general linear model, transformations and variable selection procedures
- present use of R functions for regression and interpretation of R output
Mechanics of Rigid Bodies & Fluids
This class will:
- convey the generalisation of the mechanics of single-particle systems to many-particle systems
- convey the central ideas of a continuum description of material behaviour and to understand relevant constraints
- ground students in the basic principles governing three-dimensional motions of rigid bodies
- convey how the ideas of continuum theory are applied to static and inviscid fluids.
This module will motivate the need for numerical algorithms to approximate the solution of problems that can't be solved with pen and paper. It'll develop your skills in performing detailed analysis of the performance of numerical methods and will continue to develop your skills in the implementation of numerical algorithms using R.
Stochastics & Financial Econometrics
You'll be introduced to the basic concepts of random phenomena evolving in time, from two complementary points of view: probabilistic modelling and data-driven analysis. Presentation of underlying ideas of simple stochastic processes, time series models, and the associated probability theory and statistical techniques will be covered. In addition to applications of the methods to financial and economic systems, including modelling, data analysis, and forecasting.
Communicating Mathematics & Statistics
This class provides you with experience of the skills required to undertake project work, and to communicate the findings in written and oral form using a variety of sources, such as books, journals and the internet.
Modelling & Simulation with Applications to Financial Derivatives
Here you'll get an introduction to ideas in mathematics and statistics that can be used to model real systems, with an emphasis on the valuation of financial derivatives. This module places equal emphasis on deterministic analysis (calculus, differential equations) and stochastic analysis (Brownian motion, birth and death processes). In both cases, in addition to theoretical analysis, appropriate computational algorithms are introduced. The first half of the class introduces general modelling and simulation tools, and the second half focuses on the specific application of valuing financial derivatives, including the celebrated Black-Scholes theory.
Applicable Analysis 3
This class will present the main results in Functional Analysis, give an introduction to linear operators on Banach and Hilbert spaces and study applications to integral and differential equations.
Statistical Modelling & Analysis
This class will provide you with a range of applied statistical techniques that can be used in professional life.
Fluids & Waves
You'll be introduced to the theory of Newtonian fluids and its application to flow problems and the dynamics of waves on water and in other contexts.
Finite Element Methods for Boundary Value Problems & Approximation
You'll be presented with the basic theory and practice of finite element methods and polynomial and piecewise polynomial approximation theory.
Applied Statistics in Society
You'll be introduced to a range of modern statistical methods and practices used in industry, commerce and research, and will develop skills in your application and presentation.
Mathematical Biology & Marine Population Modelling
Here you'll learn the application of mathematical models to a variety of problems in biology, medicine, and ecology. It'll show the application of ordinary differential equations to simple biological and medical problems, the use of mathematical modelling in biochemical reactions, the application of partial differential equations in describing spatial processes such as cancer growth and pattern formation in embryonic development, and the use of delay-differential equations in physiological processes. The marine population modelling element will introduce the use of difference models to represent population processes through applications to fisheries, and the use of coupled ODE system to represent ecosystems. Practical work will include example class case studies that will explore a real-world application of an ecosystem model.
Mathematical Introduction to Networks
This class will demonstrate the central role network theory plays in mathematical modelling. It'll also show the intimate connection between linear algebra and graph theory and how to use this connection to develop a sound theoretical understanding of network theory. Finally, it'll apply this theory as a tool for revealing structure in networks.
Students will learn new statistical methodology and apply it to real data from medical research studies, with an emphasis on the interpretation of the statistical results in the context of the medical problem being investigated. This skill is necessary for the application of statistics to medical data and differs from the traditional, standard interpretation of statistical textbook problems.
Learning & teaching
The following teaching methods are used in Mathematics and Statistics: lectures (using a variety of media including electronic presentations and computer demonstrations), tutorials, computer laboratories, coursework and projects.
You’ll also learn through group work and student presentations.
On completion of the programme, you’ll be able to:
- demonstrate knowledge in the main areas of mathematics
- show an understanding of the principal mathematical and educational theories and a critical understanding of one or more specialised areas
- demonstrate skills in calculation
- develop and evaluate logical arguments, presenting them and their conclusions clearly and accurately
- demonstrate problem solving skills, for example, abstracting the essentials of problems, formulating them mathematically and finding appropriate solutions
- undertake a critical analysis of data and draw conclusions from the data
- demonstrate a range of general skills including IT competency
In Mathematics & Statistics, knowledge, understanding and subject-specific skills are assessed by coursework, assignment, reports, presentations and written examinations.
BSc Mathematics entry requirements
Entry requirements are for September 2023 entry.
Required subjects are shown in brackets.
Year 1 entry: AABB/ABBBC
(Maths A, Advanced Higher Maths recommended)
ABBC (Maths A plus one of Biology, Physics, Chemistry, Computing Science or Engineering Science)
ABBB (including Maths A)
Year 2 entry: AB
Standard entry requirements*:
Year 1 entry: BBB
Year 2 entry: ABB
Standard entry requirements*:
Year 1 entry: 30
Year 1 entry: relevant HNC with strong mathematical content, B in Graded Unit
View the entry requirements for your country.
Offers are made in accordance with specified entry requirements although admission to undergraduate programmes is considered on a competitive basis and entry requirements stated are normally the minimum level required for entry.
Whilst offers are made primarily on the basis of an applicant meeting or exceeding the stated entry criteria, admission to the University is granted on the basis of merit, and the potential to succeed. As such, a range of information is considered in determining suitability.
In exceptional cases, where an applicant does not meet the competitive entry standard, evidence may be sought in the personal statement or reference to account for performance which was affected by exceptional circumstances, and which in the view of the judgement of the selector would give confidence that the applicant is capable of completing the programme of study successfully.
Lecturers and tutors are always on hand to help if you have any problems, people are really friendly which makes studying enjoyable and the facilities available to students are phenomenal.
Fees & funding
All fees quoted are for full-time courses and per academic year unless stated otherwise.
Fees may be subject to updates to maintain accuracy. Tuition fees will be notified in your offer letter.
All fees are in £ sterling, unless otherwise stated, and may be subject to revision.
Annual revision of fees
Students on programmes of study of more than one year should be aware that tuition fees are revised annually and may increase in subsequent years of study. Annual increases will generally reflect UK inflation rates and increases to programme delivery costs.
Fees for students who meet the relevant residence requirements in Scotland are subject to confirmation by the Scottish Funding Council. Scottish undergraduate students undertaking an exchange for a semester/year will continue to pay their normal tuition fees at Strathclyde and will not be charged fees by the overseas institution.
|England, Wales & Northern Ireland|
*Assuming no change in fees policy over the period, the total amount payable by undergraduate students will be capped. For students commencing study in 2022-23, this is capped at £27,750 (with the exception of the MPharm and integrated Masters programmes), MPharm students pay £9,250 for each of the four years. Students studying on integrated Masters degree programmes pay an additional £9,250 for the Masters year with the exception of those undertaking a full-year industrial placement where a separate placement fee will apply.
Course materials & costs
Class materials (lecture notes and exercise sheets) for the majority of Mathematics & Statistics classes are available free to download. For some classes, students may need access to a textbook. Textbook costs are typically in the £20-60 price range. These prices are dependent on format (e-book, soft or hardback) and whether bought new or second hand.
PVG scheme (Protection of Vulnerable Groups)
Third-year Maths and Teaching students will need to pay for the full price of a PVG membership scheme.
International students may have associated visa and immigration costs. Please see student visa guidance for more information.
Please note: All fees shown are annual and may be subject to an increase each year. Find out more about fees.
How can I fund my studies?
Students from Scotland
Fees for students who meet the relevant residence requirements in Scotland, you may be able to apply to the Student Award Agency Scotland (SAAS) to have your tuition fees paid by the Scottish government. Scottish students may also be eligible for a bursary and loan to help cover living costs while at University.
Students from England, Wales & Northern Ireland
We have a generous package of bursaries on offer for students from England, Northern Ireland and Wales:
You don’t need to make a separate application for these. When your place is confirmed at Strathclyde, we’ll assess your eligibility. Have a look at our scholarship search for any more funding opportunities.
We have a number of scholarships available to international students. Take a look at our scholarship search to find out more.
Glasgow is Scotland's biggest & most cosmopolitan city
Our campus is based right in the very heart of Glasgow. We're in the city centre, next to the Merchant City, both of which are great locations for sightseeing, shopping and socialising alongside your studies.Life in Glasgow
Studying maths helps you develop skills in logical thinking and statistical or strategic knowledge, which are valued by employers across many job sectors. Our mathematics graduates enter industries such as manufacturing, the actuarial, accountancy and banking professions, commerce and government, consultancy and education.
Many go on to work as financial analysts, accountants, operations analysts, treasury analysts, auditors and management trainees.
A degree in mathematics is desirable to a wide range of employers who recruit from any degree subject. It is also useful for those considering a more general business career.
How much will I earn?
The average (median) salary of graduates in full-time work is £20,600.
Salary potential depends on the industry you choose to work in. With experience, actuaries can earn more than £60,000 and numerical analysts £60,000. Investment analysts can earn up to £100,000 with bonuses.*
*Intended only as a guide.
Start date: Sep 2023
Mathematics (1 year entry)
Start date: Sep 2023
Mathematics (2 year entry)
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