- UCAS Code: GN12
High Flyer Programme: qualified applicants can complete course in 3 years
Ranked: Top 10 in the UK for Business & Management Studies (Complete University Guide 2021)
Study with us
- develop mathematical and statistical expertise along with the opportunity to broaden your skills in business
- Mathematics, Statistics & Business Analysis emphasises how maths can be used to solve business problems
- develop analytical expertise to support business decision-making
Why this course?
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.
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.
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.
Introduction to Economics and Business Analysis & Technology
The module will provide you with a balanced introduction to economics which will be based on a programme of systematic directed reading, supplemented by experiments and exercises undertaken in tutorials.
The module uses the innovative COREecon resources, which provides a complete introduction to economics and the economy. COREecon teaches about the economy and economics by starting from a question or a problem about the economy - why the advent of capitalism is associated with a sharp increase in average living standards, for example - and then teach the tools of economics that contribute to an answer. This innovative approach ensures that students understand how the tools of economics can help us understand the modern economy.
The second half of the module is the study of how analytical thinking, scientific method and associated tools can be used to help decision making. This Business Analysis element of the module will provide an overview of where methods and tools are widely used across a large range of industries including the manufacturing, retail, healthcare, financial services, travel, and electronics industries, as well as in local and national government.
Examples of where Business Analysis is put into practice are:
- the management of new building projects
- the design of efficient transport systems and plant layouts
- personnel scheduling
- allocation of resources and financial modelling and forecasting
This area of expertise can help to reduce costs, increase revenues, improve customer service, increase efficiency and can even save lives.
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.
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.
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.
Analysing & Improving Operations
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.
Managing Business Processes & Information Systems
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.
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.
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
Understanding & Optimising Business Systems
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.
Knowledge & Innovation Management
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.
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.
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.
You'll choose between the following projects:
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.
Project - Management Science
Dissertation - Management Science
Optional classes - list A
Statistical Modelling & Analysis
This class will provide you with a range of applied statistical techniques that can be used in professional life.
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.
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.
Modelling & Simulation with Applications to Financial Derivatives
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. The class places equal emphasis on deterministic analysis (calculus, differential equations) and stochastic analysis (Brownian motion, birth and death processes). In both cases, in additional 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.
Optional classes - list B
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.
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.
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.
Optional classes - list C
Management Science 4
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.
Business Analytics Using Data Mining
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.
Risk Analysis & Management
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.
Business Process Integration with Enterprise Resource Planning
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.
Contemporary Business Technology
This class seeks to explore the inter-relationship that exists between a theoretically grounded understanding of technology and its effect on how modern organisations adopt such technology through an increasingly changing and competitive environment. This class will build upon skills gained in previous years, whilst allowing students to generate their own knowledge through rigorous class discussion and presentations.
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 shown in brackets.
Year 1 entry: AABB/ABBBC
(Maths A, English C, Advanced Higher Maths recommended)
(Maths A, English C)
Year 2 entry: AAB
(including Maths A and Accounting or Economics A)
Minimum entry requirements:
Year 1 entry: BBB
(Maths, GCSE English Language 6/B or English Literature 6/B)
Year 2 entry: ABB
(Maths A, business subject B, GCSE English Language 6/B or English Literature 6/B)
(Maths HL6, English SL6)
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.
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.
Degree preparation course for international students
We offer international students (non-EU/UK) who do not meet the academic entry requirements for an undergraduate degree at Strathclyde the option of completing an Undergraduate Foundation year programme at the University of Strathclyde International Study Centre.
Upon successful completion, you will be able to progress to this degree course at the University of Strathclyde.
We've a thriving international community with students coming here to study from over 100 countries across the world. Find out all you need to know about studying in Glasgow at Strathclyde and hear from students about their experiences.Visit our international students' section
Fees & funding
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 2021-22, 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.
|University preparation programme fees|
International students can find out more about the costs and payments of studying a university preparation programme at the University of Strathclyde International Study Centre.
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.
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
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 in the very heart of Glasgow, Scotland's largest city. National Geographic named Glasgow as one of its 'Best of the World' destinations, while Rough Guide readers have voted Glasgow the world’s friendliest city! And Time Out named Glasgow in the top ten best cities in the world - we couldn't agree more!
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.
Find out what some of our students think about studying in Glasgow!Find out all about life in Glasgow
We're shortlisted for University of the Year 2021 by The Times and The Sunday Times Good University Guide
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.
Start date: Sep 2022
Mathematics, Statistics & Business Analysis (1 year entry)
Start date: Sep 2022
Mathematics, Statistics & Business Analysis (2 year entry)
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