Don’t worry if you’ve missed the UCAS January deadline. 

If you want to study with us in September 2018, contact us for advice about available spaces on this course.

Get in touch with our friendly admissions team on +44 (0)1752 585858 or email us at admissions@plymouth.ac.uk.

The final deadline for UCAS applications is 30 June 2018.

• This course offers modules in all key areas of mathematics, statistics and theoretical physics, including a wide choice of final year options allowing you to follow your interests and shape your future career. In the 2017 National Student Survey (NSS), 100 per cent of our final year students were satisfied with the quality of the course.*
• You will acquire skills which are highly sought after by employers: problem solving skills, knowledge of industry software packages as well as presentation and communication skills. In the 2017 NSS, 100 per cent of our final year students said that 'I have had the right opportunities to work with other students as part of my course'.*
• Our graduates find a wide range of interesting jobs or progress to postgraduate study, often winning funded places on highly contested MSc courses. Recent employers include Ernst & Young, PAREXEL, Glory Global Solutions, KPMG, PWC, GCHQ, Lloyds Banking Group, the Met Office, Towers Watson, Oxford Clinical Trials Research Unit, BT Retail.
  
• Modules are taught by lecturers who are outstanding as both teachers and researchers. In the 2017 NSS, 98 per cent of our final year students said that 'Staff are good at explaining things'. In the last UK Research Excellence Framework (2014), 68 per cent of our research papers were classified as 'World Leading' or 'Internationally Excellent’.*
• Our generous contact hours, our open door policy and small group tutorial sessions are designed to enhance and support your learning experience. Both peer-assisted learning activities and dedicated study space are provided. We use the latest technology in class and you will be equipped with a tablet PC so that you can access Podcasts and eBooks which form part of our extensive suite of online support materials.
  
• A paid placement year primes you for the career you want. Previous placement providers for our maths students have included the Department for Communities and Local Government, Eli Lilly, Fujitsu, GlaxoSmithKline and Liberty Living. This placement year is optional but highly recommended.
  
• Our course is accredited by the Institute of Mathematics and its Applications and your degree sets you on a path to Chartered Mathematician (CMath) status.
  

• Year 1
• In Year 1 you'll acquire a solid foundation through mastering calculus, linear algebra, numerical methods and programming, plus probability and statistical inference. New material includes an introduction to logic and methods of proof and the number theory underlying public key cryptography, which you use every time you purchase something online. You'll also study branches of pure mathematics such as group theory and graph theory.

  Core modules

  • BPIE113 Stage 1 Mathematics Placement Preparation

    The route to graduate-level employment is found easier with experience. These sessions are designed to assist students in their search for a year-long placement and in their preparation for the placement itself. Such placements are optional but strongly recommended.

  • MATH1601 Mathematical Reasoning

    This module introduces the basic reasoning skills needed to develop and apply mathematical ideas. Clear logical thinking is central to the understanding of mathematics. The module explores fundamental properties of prime numbers, their random generation and use in modern cryptography.

  • MATH1602 Calculus and Analysis

    This module covers key topics in calculus and analysis and prepares students for the rest of their degree. It has an emphasis on proof and rigour and introduces some multi-dimensional calculus together with the reasoning skills needed for the development of modern mathematics. Analysis is the rigorous underpinning of calculus and these key ideas are developed and applied to limits of sequences, series and functions.

  • MATH1603 Linear Algebra and Complex Numbers

    This module explores the concepts and applications of vectors, matrices and complex numbers. The deep connection between algebra and geometry is explored. The techniques that are presented in this module are at the foundation of many areas of mathematics, statistics, physics, and several other applications.

  • MATH1605 Probability with Applications

    An understanding of uncertainty and random phenomena is becoming increasingly important nowadays in daily life and for a variety of fields. The aim of this module in probability is to develop the concept of chance in a mathematical framework. Random variables are also introduced, with examples involving most of the common distributions and the concepts of expectation and variance of a random variable.

  • MATH1610 Numerical and Computational Methods

    This module provides an introduction to appropriate mathematical software, computational mathematics and creating simple computer programs. Students will use mathematical software interactively and also write programs in an appropriate computer language. The elementary numerical methods which underlie industrial and scientific applications will be studied.

  • MATH1611 Geometry and Group Theory

    This module will introduce the foundations of group theory, elementary geometric topology, and Euclidean geometry.

• Year 2
• In Year 2 you'll expand your knowledge with topics including vector calculus, real and complex analysis, differential equations, transform theory and mathematical statistics. A case studies module introduces operational research, the branch of mathematics developed for better management and decision making, and powerful Monte Carlo methods for simulating complex problems.

  Core modules

  • BPIE213 Stage 2 Mathematics Placement Preparation

    These sessions are designed to help students obtain a year-long placement in the third year of their programme. Students are assisted both in their search for a placement and in their preparation for the placement itself.

  • MATH2601 Advanced Calculus

    In this module the geometrical and dynamical concepts needed to describe higher-dimensional objects are introduced. This includes vector calculus techniques and new forms of integration such as line integration. Students also explore the relations between integration and differentiation in higher dimensional hyperspaces. This knowledge is applied to various real world problems.

  • MATH2602 Statistical Inference and Regression

    The module provides a mathematical treatment of statistical inference, including confidence intervals and hypothesis testing. Methods of estimation are explored, focusing on maximum likelihood estimation. The module also demonstrates the underlying mathematical theory of the general linear model, through a variety of applications, using professional software.

  • MATH2603 Ordinary Differential Equations

    The module aims to provide an introduction to different types of ordinary differential equations and the analytical and numerical methods needed to obtain their solutions. Extensive use is made of computational mathematics packages. Applications to mechanical and chemical systems are considered as well as the chaotic behaviour seen in climate models.

  • MATH2604 Mathematical Methods and Applications

    Vector calculus is extended to higher dimensions and applied to a range of important scientific problems primarily from classical mechanics and cosmology. Differential and integral calculus is applied to the solution of differential equations and the orthogonal functions bases are constructed. The crucial mathematical concepts of integral transforms (Fourier and Laplace) and Fourier series are introduced.

  • MATH2605 Operational Research and Monte Carlo Methods

    This module gives students the opportunity to work on open-ended case studies in operational research (OR) and Monte Carlo methods, both of which are important methods in, for example, industry and finance. It allows students to work on their own and in teams to develop specific skills in OR and programming as well as refining their presentation and communication skills. The skills in computational simulation developed in this module have many application.

  • MATH2606 Real and Complex Analysis

    This module deepens the student’s understanding of real analysis and introduces complex analysis. The important distinction between real and complex analysis is explored and the utility of the complex framework is demonstrated. The central role of power series and their convergence properties are studied in depth. Applications include the evaluation of improper integrals and the construction of harmonic functions.

• Optional placement year
• You'll have the opportunity to participate in an optional but highly recommended placement year, providing valuable paid professional experience and helping make your CV stand out. Typically students are paid around £17,000 and placement providers have included the Department for Communities and Local Government, Fujitsu, GlaxoSmithKline, Vauxhall Motors, VirginCare, Visteon and Jagex Games Studio.

  Optional modules

  • BPIE331 Mathematics and Statistics Placement

    A 48-week period of professional training is spent as the third year of a sandwich programme while undertaking an approved placement with a suitable company. This provides an opportunity for the student to gain experience of how mathematics is used in a working environment, to consolidate their previous study and to prepare for the final year and employment after graduation. Recent placement providers include GSK, the Office for National Statistics, NATS (air traffic control) and VW Group.

• Final year
• The final year focuses on individual and group project modules offering a chance for you to study a topic of your choice in depth. Also you may opt to study a school-based placement module. You’ll additionally have a wide choice of modules which cover a varied range of topics from pure and applied mathematics and operational research, to theoretical physics and statistics.

  Optional modules

  • MATH3601 Mathematical Sciences in Context

    This module is designed to be an alternative to the individual project. In the module students perform structured investigations on a variety of advanced topics in mathematics and statistics. Students give oral presentations and write up a journal style article on their work. Some of these articles have been published in the University of Plymouth’s Student Scientist journal.

  • MATH3603 Professional Experience in Mathematics Education

    This module provides an opportunity for final year students to gain experience in teaching and to develop their key educational skills by working in a school environment for one morning a week over two semesters.

  • MATH3604 Geometry and Algebra

    A review of group theory leads into an exploration of plane affine, hyperbolic, and projective geometries, all from the Kleinian point of view. Then an introduction to rings and fields is given with applications in geometry emphasised. These topics are key ideas in the study of pure mathematics.

  • MATH3605 Partial Differential Equations

    This module introduces partial differential equations using real-life problems. It provides a variety of analytic and numerical methods for their solution. It includes a wide range of applications including heat diffusion and the Tsunami wave.

  • MATH3606 Classical and Quantum Mechanics

    All of physics and a large part of applied mathematics is based on classical mechanics and its extension to quantum theory. This module introduces key ideas of these topics to students with a mathematics background. An overarching theme is the key role of symmetry, both for classical motion and quantum behaviour.

  • MATH3609 Optimisation, Networks and Graphs

    This module introduces the mathematics of continuous and discrete optimisation. It provides the theoretical background and practical algorithmic techniques required to model and solve a diverse range of problems.

  • MATH3611 Electrodynamics and Relativity

    This module introduces Maxwell's theory of electromagnetism and Einstein's theory of special relativity. It includes a wide range of applications of electromagnetism, the Lorentz transformations and some of the apparent paradoxes of relativity together with their resolution. It also explains why E = mc^2.

  • MATH3612 Dynamical Systems

    This module presents an introduction to the basic concepts and techniques needed to analyse nonlinear dynamical systems modelled by differential equations and difference equations. Both regular and chaotic dynamics are explored.

  • MATH3613 Data Modelling

    This module provides an employment relevant tool box of statistical modelling techniques and a rigorous treatment of the underlying mathematics. The Bayesian framework for statistical inference is developed and compared with the classical approach. Important computational algorithms, including Markov Chain Monte Carlo, are described. Application-rich modelling problems are considered.

  • MATH3614 Medical Statistics

    The content includes the design and analysis of clinical trials, including crossover and sequential designs and an introduction to meta-analysis. Epidemiology is studied, including case-control and cohort studies. Survival analysis is covered in detail. Computer packages are used throughout.

  • MATH3616 Professional Experience in Industry

    This module provides an opportunity for students to gain experience in applying mathematics in a commercial setting by undertaking a summer placement. Students develop their skills in written and verbal communication, listening, problem solving, time management, teamwork and leadership. Recent summer placement providers include Babcock International, BMW Group, Chess Dynamics Ltd and South West Water.

  • MATH3623 Financial Statistics

    This module introduces students to the concepts and methods of financial time series analysis and modelling and to a variety of financial applications. The module reviews the necessary univariate and multivariate time series models and inferential techniques. Model selection, forecasting and the ‘curse of dimensionality’ problem for high dimensional modelling are treated both analytically and computationally. The R programming language is widely used in this module.

  • MATH3628 Project

    Students who have identified a topic of particular interest have the opportunity to study it in a final year project. Students work individually and independently, with help and advice from a supervisor, on the chosen topic. The project is assessed through presentations and the preparation of a dissertation. This is a major piece of work and the project counts as two modules

  • MATH3629 Fluid Dynamics

    Fluid flow problems are at the heart of systems ranging from weather forecasting and climate models to hydroelectricity generation and aerodynamics. They are all formulated mathematically as systems of partial differential equations. These are then solved and the results interpreted for a mixture of theoretical and practical examples of both inviscid and viscous fluid flows. Applications studied include: aeronautics, ocean waves and a variety of industrial topics.

Every undergraduate taught course has a detailed programme specification document describing the course aims, the course structure, the teaching and learning methods, the learning outcomes and the rules of assessment.

The following programme specification represents the latest course structure and may be subject to change:

BScMathematics ProgrammeSpecification September2018 0153

UCAS tariff

120 - 128