Why this course?
What you’ll study
Mathematics and statistics are used in business every day. The analysis of how business works, how data can be effectively used and how we can optimise business practices are all examples of where the use of mathematics and statistics can help business to be more successful and they are all important aspects of the science of management.
This area, management science, is also known as operational research (OR) and is concerned with applying quantitative techniques and the modelling of business problems to management decision-making and planning.
Our joint degree, offered in collaboration with Strathclyde Business School, bridges the gap between management science, mathematics and statistics.
You'll have the opportunity to develop mathematical and statistical expertise at the same time as broadening your skills base in an award-winning Business School.
The course emphasises the great applicability of mathematics to solving practical problems meaning that you'll learn the skills that employers need.
Our flexible degree structure enables transfer between courses and there are opportunities to study abroad.
Learn more about the opportunities available in mathematics & statistics and management science.
The Department of Mathematics and Statistics has teaching rooms which provide students with access to modern teaching equipment and are conducive to student learning whilst the undergraduate common room allows students a modern and flexible area which is used for individual and group study work and also a relaxing social space.
Current students are taking the following classes, and we expect the syllabus to be similar to this in future years.
Introduction to Calculus
You'll study the basic concepts and standard methods of mathematical notation and proof, polynomial equations and inequalities, sequences and series, functions, limits and continuity, differentiation and integration.
Applications of Calculus
Geometry & Algebra with Applications
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.
Statistics & Data Presentation
This class will introduce you to vectors and matrices, along with the idea of mathematical modelling through their application to real-world problems.
Foundations of Business Analysis & Technology
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.
Business Analysis & Technology is the study of how analytical thinking, scientific method and tools can be used to help decision making. This class aims to introduce a variety of analytical methods that form the basis of analysing any business problem as well as provide students with an overview of technological change and how it affects all aspects of an organisation.
The aims of this class are:
- to raise awareness of the real world problems encountered by industry that can be solved through management science methodology
- to develop an understanding of the tools and techniques used by business analysts
- to provide students with an awareness of why and where organisations use technology
- to highlight the integrative role of technology within organisations
- to demonstrate the dynamic nature of technology
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.
Probability & Statistical Inference
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.
Mathematical & Statistical Computing
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.
Analysing & Improving Operations
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.
Managing Business Processes & Information Systems
This class is one of the two undergraduate Business Analysis & Technology classes before the Honours year that apply various approaches to operations management problems. Following on from the fundamentals in the first year class, this class introduces you to the subject of operations management in detail and provides opportunity for you to apply some of the basic decision analysis techniques, including simulation, in this context.
This class forms a bridge between the first year class and more advanced classes in Enterprise Resource Planning, Business Process Outsourcing, the role of ICT in business environment, etc.
The class will seek to combine conceptual and technical skills, and it will provide the basis for a series of classes in third and Honours years, especially in areas of Business Process Integration with ERP, organisational innovation and E-commerce.
Inference & Regression Modelling
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.
Understanding & Optimising Business Systems
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
Knowledge & Innovation Management
The first part of the course will introduce and build experience in two problem structuring methods, SODA and Soft Systems Methodology. The second part will establish an overall understanding of how supply chains work as well as appropriate modelling approaches to address various operational challenges. The third part of the course will introduce basic mathematical optimisation modelling and present how it can be used to tackle problems in different business systems, including applications in supply chains.
The fourth and final part of the course will introduce the students to the ideas of Multi-criteria Decision Analysis to make students aware of the importance of carefully defining objectives when intervening in business systems. Overall, the course will equip students with the qualitative and quantitative analytic skills and techniques in order to make action recommendations for performance improvements in complex business systems.
In this class, students will develop a comprehensive picture about knowledge and innovation. It goes to the very basis of what constitutes knowledge and knowledge work, and, based on this, develops the notion of creativity, as creation of new knowledge, and subsequently conceptualises innovation as new value created from the new knowledge.
Choose from the classes below and a list of additional Business Analysis classes.
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.
Stochastics & Financial Econometrics
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.
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.
You'll choose between the following projects:
Communicating Mathematics & Statistics
Project - Management Science
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.
Optional classes - list A
Statistical Modelling & Analysis
Applied Statistics in Society
This class will provide you with a range of applied statistical techniques that can be used in professional life.
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.
This class will cover the fundamental statistical methods necessary for the application of classical statistical methods to data collected for health care research. There will be an emphasis on the use of real data and the interpretation of statistical analyses in the context of the research hypothesis under investigation. Software packages such as Minitab will be introduced.
Optional classes - list B
Modelling & Simulation with Applications to Financial Derivatives
Applicable Analysis 3
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.
Fluids & Waves
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.
Finite Element Methods for Boundary Value Problems & Approximation
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.
Mathematical Biology & Marine Population Modelling
You'll be presented with the basic theory and practice of finite element methods and polynomial and piecewise polynomial approximation theory.
Mathematical Introduction to Networks
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.
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.
Optional classes - list C
Management Science 4
Business Analytics Using Data Mining
An important aspect of this class is the experiential learning element, where you'll work in teams on management science projects, directly for external clients.
The clients will introduce their problems, provide information during the project, and listen to your recommended solutions. These client projects will be chosen to highlight the differing nature of individual practice, allowing comparisons between qualitative and quantitative projects to be explored.
Alongside the experiential learning will be a reflective element, which will focus on issues relating to client, consultant relations and implementation of management science, as well as addressing more conceptual issues relating to problem structuring, modelling, data collection, and choosing and mixing methods in the light of your growing experience.
Professional and ethical considerations will be highlighted, introducing you to the areas of agreement and debate within the profession. This class will also include an individual or small group project, where you'll select a technique or method they haven’t previously studied to research in more depth, mirroring professional development that they will undertake in practice. This component of the class will be managed through learning contracts.
Risk Analysis & Management
This class builds upon students understanding of information systems. It'll provide you with the opportunity to develop analytical approaches for mining data using commercial software that'll be intellectually challenging and useful.
This class focuses on the methods used for mining data, complementing the other Honours classes that provide business context and processes.
Business Process Integration with Enterprise Resource Planning
Identifying and managing risk is a fundamental skill required by managers. Many models exist for supporting risk assessment and this is a major area of interest within the Management Science department.
This class will introduce you to the general concepts of risk and common measures used as well as considering ways of modelling and interpreting technical risk within the context of managing complex systems in areas such as transportation, aerospace, health.
It'll develop knowledge and skills introduced in years 1-3 in operations, statistics and modelling classes by integrating and extending them within the context of risk assessment.
This class investigates the application of sophisticated business technology systems to the management and, more particularly, integration of business processes.
In doing so, it builds directly on the knowledge and skills acquired as part of Management of Business Processes and, in a more indirect manner, on classes like Technological and Organisational Innovation, Information Systems in the Knowledge Economy, and Information Systems Support for Managers.
In Mathematics & Statistics, the course incorporates a range of assessment types. Continuous assessment during some classes and summative assessment at the conclusion of classes both contribute to the overall assessment and are used to formally measure achievement in specified learning outcomes.
Understanding, knowledge and subject-specific skills are assessed by coursework assignments, reports, presentations and written examinations. Formative assessment is used to provide feedback and inform student learning. Management Science allows for considerable diversity in assessment methods relative to the specific learning outcomes.
The majority of classes involve a final written examination, supplemented by one or more forms of individual and/or group coursework. In some cases, students can obtain exemption from the final examination on achieving a specified mark for their coursework (often in conjunction with satisfying requirements for attendance).
Where examination is part of the assessment for a class, the examination is normally scheduled at the end of the semester in which the class is taught.
The methods of assessment for classes are consonant with the learning objectives of the class; and a range of traditional and innovative techniques are used, for example: unseen examinations, business reports, case studies, essays, presentations, individual and group projects, learning journals and peer assessments.
Students normally have one opportunity to be re-assessed for a failed class. Where this is by written exam, this normally takes place during the summer.
Learning & teaching
The following teaching methods are used in Mathematics & Statistics: lectures (using a variety of media including electronic presentations and computer demonstrations), tutorials, problems classes, computer laboratories, coursework, projects.
You'll also learn through group work in problem solving and collaborative student presentations.
Management Science teaching includes more traditional lectures, tutorials, and seminars alongside student-centred methods such as team-based action learning projects, online materials, and interactive sessions using personal response systems. Emphasis is placed on using those methods most suited to the specific learning outcomes, subject context, class level and size.
Our business partners are often involved in the delivery of classes and/or assessment of student presentations.
On completion of the programme, you'll be able to:
- demonstrate subject knowledge which covers many of the main areas of mathematics, statistics and management science;
- show an understanding of the principle mathematical and management theories and a critical understanding of one or more specialised areas through applying a range of concepts and principles in loosely-defined contexts, showing effective judgement in the selection and application of tools and techniques;
- demonstrate a good level of skill in calculation and manipulation of the material within this body of knowledge;
- develop and evaluate logical arguments, presenting them and their conclusions clearly and accurately;
- demonstrate a range of problem-solving skills eg abstracting the essentials of problems, formulating them mathematically and obtaining solutions by appropriate methods;
- undertake a critical analysis of data and draw conclusions from the data
- demonstrate a range of appropriate general skills including IT competency.
Required subjects are indicated following minimum accepted grades.
Year 1 entry: AABB or ABBBC (Maths A, English C, Advanced Higher Maths recommended)
Year 2 entry: AAB (including Maths A and Accounting or Economics A)
Year 1 entry: BBB (Maths A, GCSE English Language B OR English Literature B)
Typical entry requirements: ABB
Year 2 entry: ABB (Maths A, Business subject A, GCSE English Language and English Literature C)
Typical entry requirements: AAA
Year 1 entry: 32
Year 2 entry: 34 (Maths HL6, English SL5)
Year 1 entry: relevant HNC with strong mathematical content, B in Graded Unit
Year 2 entry: not offered
We want to increase opportunities for people from every background. Strathclyde selects our students based on merit, potential and the ability to benefit from the education we offer. We look for more than just your grades. We consider the circumstances of your education and will make lower offers to certain applicants as a result.
Find out if you can benefit from this type of offer.
Find out entry requirements for your country.
Degree preparation course for international students
We offer international students (non EU/UK) who do not meet the entry requirements for an undergraduate degree at Strathclyde the option of completing an Undergraduate Foundation year programme at the International Study Centre.
You can also complete the online application form, or to ask a question please fill in the enquiry form and talk to one of our multi-lingual Student Enrolment Advisers today.
Fees & funding
How much will my course cost?
Rest of UK
Assuming no change in Rest of UK fees policy over the period, the total amount payable by undergraduate students will be capped. For students commencing study in 2017/18, this is capped at £27,750 (with the exception of the MPharm and Integrated Masters courses); 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.
International Study Centre
Please find information about the student fees for university pathway programmes on the International Study Centre (ISC) website.
Mathematics & Statistics
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.
£40 returnable deposit for PRS handsets.
Course materials & costs
There is no charge for course materials.
Placement & field trips
For students working on their final project, travel costs are usually met by clients. On the rare occasions where travel costs are not met by the client, student costs will depend on location and frequency of travel.
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 and the EU
If you're a Scottish or EU student, 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.
For more information on funding your studies have a look at our University Funding page.
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.
International Students (Non UK, EEA)
We have a number of scholarships available to international students. Take a look at our scholarship search to find out more.
We have a wide range of scholarships available. Have a look at our scholarship search to find a scholarship.
Graduates of the Mathematics & Statistics Department enter a wide range of employment as the advanced numeracy, analytical and problem-solving skills are in high demand across a range of sectors.
Our graduates are working in from the manufacturing and service industries, the actuarial, accountancy and banking professions, commerce and government, consultancy and education.
Our graduates and go on to become investment analysts, numerical analysts, statisticians, actuaries, managers and teachers.
Graduates who have specialised in management science have excellent problem-solving, numeracy, business awareness and teamwork skills and in previous years have been employed across the private and public sectors as analysts.