Mathematical thinking is an approach to mathematics in terms of not only solving problems but in terms of constructing proofs, presenting convincing rigorous arguments and the ability to generalise with abstraction. MAU401 begins with a slow introduction to logic and a review of the various types of proof together with their logical foundations. Definitions are then discussed with detailed examples of rigorous deductions, leading to the very beginnings of analysis. Limits of sequences and functions are carefully discussed as well as continuity and convergence criteria of series will be investigated. If time permits, various notions of algebraic abstract structures are also introduced together with a highlight of their applications. An important aspect of Mathematical Thinking is students must feel part of the subject and its community, to take active ownership in properly engaging with mathematics and to foster an approach to mathematics and its applications that are insightful, well planned, neat, rigorous and rewarding. The course will also highlight the strong historical heritage of mathematics and expose students to some important individuals of mathematics as well as reviewing accessible mathematical literature.
A modern graduate needs to operate in a world where there are a number of standard software tools that are expected to be used with confidence, and modern mathematics graduates need to exploit such tools much further for the solution and presentation of complex mathematical and statistical problems. MAU402 introduces the mathematical and typesetting capabilities of MS Office (Microsoft Mathematics add-in) and the mathematical and statistical capabilities of Excel. LaTeX is also introduced as well as other useful tools and hardware (such as iPad, tablet PC,…) for the professional presentation of high quality documents containing mathematical content. There is also a brief introduction to the use of Maxima/Matlab as scripted programming languages. Using such tools, students will work in small groups to offer and argue a viable solution to a problem, and to present their findings both orally and in the form of multimedia posting within a social forum. The mathematical professional also needs to promote their subject, to explain its power, universality and beauty. The course will finish by establishing a strong commitment from students to promote mathematics and its uses.
MAU403 is an important and detailed review and reminder of essential and important foundational mathematics, especially themes related to algebra and calculus, for students who are new to higher education mathematics and who require a firm foundation and common grounding in level 4 beginning mathematical techniques. The course prepares students for further mathematical studies in higher education and introduces computer algebra as a vital and important tool that not only solves problems but also helps students learn and simulate mathematics. The course will also have a strong support aspect to identify early weak areas and to strengthen areas identified through online computer marked assignments before an end of course examination.
Mathematical methods such as first order and more detailed second order differential equations are reviewed and applied, including vector algebra in three dimensions. Applications are considered related to a variety of situations, such as mechanics and motion, physics, finance, economics and other applied areas. The mathematical modelling process is introduced, applied and validated. An important approach of MAU404 is the use of computer algebra (and/or other tools) to simulate mathematical models and situations.
MAU405 introduces the notion of linear structures and their representation as matrices. Matrix algebra and manipulation will be formalised and linear transformations, matrix reduction techniques, vector spaces, orthogonality, determinants, eigenvalues and eigenvectors are developed together with a clear discussion of their relationship and meaning. Applications are then developed to coupled-linear systems, coupled first and second order linear differential equations and their solutions in terms of eigenvectors and eigenvalues are developed and simulated, including the illustration of normal modes. Throughout the course there will be a strong use of computer algebra and other software to check and test ideas, to simulate solutions, and to solve problems that are too large to solve by hand. If time permits, applications in diverse areas such as physics, business and bioinformatics will be demonstrated to illustrate the far reaching power and applicability of linear algebra.
MAU406 focus is on data, data collection, unbiased sampling, displaying data and reaching conclusions about populations based on samples and various statistical tests, and developing a clear understanding of variability and statistical thinking. The course begins with a review of probability and chance of both discrete and continuous systems and develops an understanding of their mean, standard deviation and other measure of central tendency and variation. The modelling of variation is further developed including both discrete and continuous models. The central limit theorem is firmly established together with applications based on confidence intervals, hypothesis testing, nonparametric statistical tests, regression, and correlation analysis. MAU406 will focus on applied statistics using appropriate software with carefully and clear interpretation of results and conclusions.
This module aims to equip students with the knowledge and self-management skills to make informed choices in preparing for work placement and the transition to employment or further study on graduation. Learners will be provided with the opportunities to develop awareness of the workplace, identify different career and study options, recognise and articulate their own experience, accomplishments and talents and plan and implement career management strategies for the short and long term.
- G100 Course Code
- 3-4.5* Years
- 96 Typical UCAS Tariff
This degree is accredited by the Institute of Mathematics & its applications (IMA).The IMA actively supports students of mathematics as well as supporting universities to ensure that their mathematics related courses are relevant and up to date. An IMA validated degree programme is assured in terms of teaching, learning and support.
Problem solving and mathematical modelling are fundamental themes of the course – representing real world problems in a mathematical form and then using appropriate methods and techniques to simulate and analyse, translating results back from mathematics to the actual problem together with an appropriate interpretation. You will build on the mathematics that you have already studied, further extending your knowledge of calculus and algebra. You will also be introduced to mathematical modelling and simulation, including statistics, and learn how to approach building a mathematical representation to simulate real world problems.
Practicing mathematicians make extensive use of sophisticated software to analyse complex problems. During the first year you will be introduced to software tools which handle the drudgery of calculation, allowing you to focus on the higher level mathematical issues related to the appropriateness and reliability of the model being used.
Please note that the course information on this web page reflects our offer for September 2022. This course is subject to successful re-validation for September 2023 entry, and the website will be amended in due course for September 2023 entry.
- An ideal first degree
- A focus on using mathematics to solve real problems
- Using industry standard software to analyse complex situations
- An extensive final year project applying mathematics in an area of your own choosing
- IMA Accreditation (Institute of Mathematics and its Applications)
- Credit bearing work placement in a mathematical environment
- Development of skills to communicate findings with both those with no advanced mathematical knowledge and specialist mathematicians
Mathematics is playing an increasingly important role in modern life in areas ranging from internet security to medical imaging, from data analytics to telecommunications. And, of course, it remains important in traditional areas such as finance and teaching. Mathematicians are in high demand.
The BSc Mathematics programme at Newman will equip you with the cognitive and practical problem solving skills to successfully apply mathematical thinking in a wide range of situations.
In your first year you will study Mathematical Thinking to develop your logic and proof skills to ensure your approach to mathematics is much more formal and rigorous as well as taking modules that will develop mathematical methods and modelling skills. This will be followed by The Mathematical Professional to develop software skills and Linear Algebra and Probability and Statistics to give you an overall firm foundation in pure mathematics, applied mathematics and statistics. The various modules will also introduce a number of useful mathematical software packages to help you solve and check problems and will also allow you to experiment with mathematical ideas.
During your second year you will build on your first year modules by taking further calculus, statistics and modelling modules as well as developing further and deeper topics into pure mathematics and research methods for mathematicians. Optimization is also extensively discussed as well as further numerical methods to aid in solving equations and problems that cannot be solved exactly.
In the final year you will develop further techniques in the areas of complex analysis, graph theory, data science and partial differential equations and you will undertake an extended capstone project to be completed over two semesters that will bring together all your accumulated mathematical knowledge and skills.
The course is assessed using a combination of examinations, projects, presentations and continuous assignments.
The course will prepare you for a graduate role in a rapidly changing world. Graduates with mathematical and statistical skills are highly sought after in a wide range of industries, particularly if they are able to communicate clearly with those who are not mathematicians. Typically, mathematics graduates find employment in finance, computing, manufacturing, pharmaceutical industry and teaching. However, the list of sectors employing mathematicians is continually increasing. The growing volume and importance of data means that the number and range of ‘analyst’ roles is ever increasing – and mathematicians are ideally placed to fill such roles. In addition this degree course is also a strong academic base for those interested in studying at postgraduate level.
Newman University is located in Britain’s second city – Birmingham. With one of the youngest city populations in Europe, it is a vibrant and dynamic place to study.
Studying at Newman University, you have the advantage of being near to the city, but living in, or commuting to peaceful and comfortable surroundings on campus.
Birmingham has lots of wonderful places to dine out with a range of different cuisines. Places where you can dine out include; Brindley Place, Mailbox and Hagley Road (just 10 minutes’ from Newman).
Whether you like to go to; the theatre, gigs or clubs, or enjoy: sports, shopping visiting art galleries or exhibitions – Birmingham will not disappoint and you will be spoilt for choice!
Getting around Birmingham is easy via train, bus or by car. Birmingham has excellent transport links to the rest of Britain, making it easy for those weekend getaways!
Why not explore the city for yourself by visiting one of our Open Days?
Want to find out more about Birmingham? Then take a look at some Birmingham City Secrets.
You must achieve at least 96 UCAS points including a minimum of CC at A level or equivalent (e.g.MM at BTEC Diploma; MPP at BTEC Extended Diploma) towards the total tariff.
Access Students can achieve the requirements with the following combination of Distinction, Merit and/ or Pass grades at level 3 achieved from a completed Access course. 96 UCAS Points: D21-M3-P21; D18-M9-P18; D15-M15-P15; D12-M21-P12; D9-M27-P9; D6-M33-P6; D3-M39-P3; D0-M45-P0.
Five GCSEs at grade 4 (or C) or above (or recognised equivalents), including English Language, and a A Level (Grade C or above) in Mathematics are also required.
The University is not licenced by the UK Government to sponsor migrant students under the Student route and is therefore unable to accept applications from international students at present.
Applying Direct Option
You can apply direct to Newman University for the full-time route for this course if you have not previously applied to Newman University through UCAS and you are not applying to any other universities.
N.B. will need to enter ‘New User’ account details when first accessing this portal.
If you have any questions regarding entry onto this course please contact our friendly and helpful admissions team via our Admissions Enquiry Form
The full-time course fee for September 2023 is £9,250 per year.
The part-time course fee for September 2023 is £5,300 per year.
The University will review tuition fees and increase fees in line with any inflationary uplift as determined by the UK Government, if permitted by law or government policy, in subsequent years of your course. It is anticipated that such increases would be linked to RPI (the Retail Price Index excluding mortgage interest payments).
Find out more about the other additional costs associated with our undergraduate degrees.
Mathematics graduates at Newman are expected to have a good exposure to the formalities and rigour of mathematics, as well as having the ability to explain, communicate and illustrate such formalities using appropriate tools. The formalities will be illustrated with student developed geometric simulation, which will be the main key to penetrate important research skills of mathematicians. MAU500 develops an approach to the study and practice of formal mathematics, its rigour and the importance of proof and clarity. Building on level 4 modules, this module goes deeper into levels of rigour and revisits in a much stronger way the epsilon-delta definition of limits, continuity, differentiability and Riemann integration. Such formal aspects will be reinforced via the student development of simulation models. Appropriate computer programming languages and/or software will also be exploited to support simulation of concepts.
MAU502 introduces multivariable calculus, vector calculus and various differential equations The course begins with a discussion of functions of severable variables, partial derivatives, directional derivatives and “The Derivative” for a function from to , classifying stationary points, classifying stationary points using eigenvalues, equilibrium theory, vector calculus, polar and spherical coordinate systems and multiple integrals. Detailed applications are also carefully illustrated. More complicated differential equations compared to previous modules are motivated and discussed, including various series solutions of differential equations and Sturm-Liouville problems if time permits. The focus of MAU502 is to apply advanced calculus techniques to solve applied problems.
Understanding and modelling data and its variation is an important application of statistics and is vitally important with applications in the sciences, technology sector, engineering, business and the social sciences. Statistics that has already been studied will be extended and applied to analyse applied linear and multilinear regression models together with an emphasis on the clear communication and interpretation of results and conclusions. Data transformations will also be exploited together with variable screening to optimize the fit of regressions models, including the general testing and verification of models and their applications and limitations.
The focus of MAU504 will be mathematical modelling of a wide range of applications using difference equations and ordinary differential equations. Both discrete and continuous dynamical systems are also considered, including situations exhibiting the on-set of chaos. Numerical methods are motivated that begin with simple numerical solution techniques such as Taylor series and truncation methods. Euler’s and associated methods are then introduced including Rungee-Kutta methods. Stability and error analysis are considered and the numerical analysis of nonlinear systems is formulated. Simulation is a key approach of the module together with practical and robust solution methods. A strong understanding and control of errors and error analysis is also developed and applied.
Optimization is a key and important mathematical theme as many applied mathematical problems are concerned with maximizing or minimizing some expression or quantity. MAU505 will begin with linear optimization methods and applications. After a review of matrix and matrix iterative methods, simplex methods and linear programming techniques are introduced and for large scale problems the more modern interior point method is reviewed and applied. The course goes on to discuss nonlinear optimization, including topics such as gradient and non-gradient search methods, efficiency methods, constraints including inequality constraints. An important approach to the course is an emphasis on applications and the use of computers and/or computer algebra to solve problems that could not be solved otherwise.
Mathematics graduates at Newman are expected to have a good exposure to the formalities and rigour of mathematics, as well as having the ability to explain, communicate and illustrate such formalities using appropriate tools. The formalities will be illustrated with student developed geometric simulation, which will be the main key to penetrate important research skills of mathematicians. MAU520 develops an appreciation of the value and importance of study and practice of formal mathematics, its rigour and the importance of proof and clarity. Building on MAU500, this module develops abstract notions such as metric spaces, topology and group theory. Such formal aspects will be reinforced via the development of simulation models together with a discussion on the formal differences between simulation and proof. Appropriate computer software and/or programming languages will also be exploited to support simulation models.
This year-long module offers learners the opportunity to apply and explore knowledge within a work-based context, through the mode of work place learning. The placement supervisor in the work place will negotiate the focus for the learner’s role on placement, with the learner. Students complete 100 hours in the work setting. The learner will reflect critically on different dimensions of the work place setting. This module provides an opportunity for students wishing to attain National Professional recognition with the Teaching and Learning Academy (TLA) to complete an AMTLA project.
The module builds on prior learning and offers students the opportunity for further development of skills and knowledge learnt throughout the course with the opportunity to further develop a mathematical topic of particular interest. The dissertation involves the development of an independent research project. The project must include the analysis of related literature and the application of applied or theoretical principles.
This module offers students the opportunity to build on their level 5 work placement through the more developed application of a negotiated work-based research project. Students will agree with their placement tutor and workplace mentor a brief for a project which addresses a need within the organisation. Learners should complete a minimum of 100 hours in the work place. It is in the spirit of this module that wherever possible, the focus will be on social or community / sustainable development.
Complex analysis is firstly considered including topics such as the complex number field, complex functions, sequences and subsets, limits, continuity, differentiation, Cauchy Riemann equations, integration, the Cauchy integral theory, Taylor and Laurent series, singularities, the residue theorem and applications to the evaluation of real integrals and series. The module then considers some applications of complex analysis, in particular integral transforms together with their application, including Laplace transformations and Fourier transforms. If time permits, applications of complex analysis to two dimensional fluids will be discussed.
Graph theory and networks is a detailed study of the mathematics associated with connected systems. It is a branch of discrete mathematics with strong links to combinatorics. After formalising basic graph theory such as graphs, digraphs, tress, connectivity, network flow, matching, planer graphs, vertex and edge colours, the important role and connection with algorithmic graph theory is established. Applications are then developed to diverse areas such as scheduling, circuit analysis, geometric design, kinetic design and block design.
Machine learning is concerned with the development of algorithms that learn to recognise patterns in data and use these to make intelligent decisions. Examples include spam detection, credit card fraud detection and product recommendation. This module aims to introduce students to the mathematical foundations for machine learning and a set of approaches to address data driven problem solving.
MAU605 is a natural extension of both MAU502 and MAU505. The core theme is boundary value problems of partial differential equations including connections with special types of ordinary differential equations. A classification is first made of various types of partial differential equations including various methods of solution such as the method of characteristics and separation of variables. Both the heat and wave equations are explored and applied, including the associated Laplace equation. A number of solution approaches and techniques are established including relevant solutions of associated ordinary differential equations, Fourier series solutions and associated eigenvalue and eigenvector approaches. Linear operator approaches are also firmly established including related Sturm-Liouville problems.
Strategic management is central to the operation of a variety of businesses in different sectors and environments. The creation of a strategy and the management of its implementation are important in developing businesses that can create and sustain a competitive advantage. The management of strategy involves coping with uncertainty, change and complexity. This module looks at how strategy is currently practiced in a wide variety of contexts from commercial and entrepreneurial to social and not-for-profit. The module will provide students with the necessary managerial tools and techniques required in order to undertake a strategic analysis & review of their organisational environment and develop a suitable plan to lead the organisation into the future. It also encourages exploration of and a critical approach to the key concepts that underpin strategic management and the tools managers use to analyse their environment, frame choices and put the resulting strategies into action.
This module aims to equip the students with the knowledge and skills expected of the financial manager in relation to investment, financing and dividend policy decisions. It will provide students with the necessary managerial tools and techniques required in order to undertake a strategic analysis and review of their organisational environment and develop a suitable plan to lead the organisation into the future.
In this module, students have the opportunity to learn and reflect upon how mathematics is taught in schools, both as a passive observer and an active participant. Students will act as ambassadors for the subject by sharing their knowledge of and passion for mathematics, motivate learners and hopefully inspire them to understand an aspect of the beauty and joy of mathematics. Working alongside an in-service mathematics teacher, students will have the opportunity to communicate computer science concept(s) to learner(s) and reflect upon this experience. This experience will enable students to develop transferable employability skills; such as organising and planning, communication, and working within a professional team; within a professional environment. For those students who wish to pursue a career as a mathematics teacher, then this module provides a vehicle for gaining valuable insight into not only how mathematics is taught in schools but also the role and responsibilities of a mathematics teacher. In order to take this module, students will be required to attend orientation training regarding working with learners and conducting themselves within a school-based setting. This orientation will be held in the first semester of the final year of this programme.
The module will look at using technology to both teach and assess mathematics. Students will explore and develop interactive applets to illustrate mathematics and assess mathematics.
The module will look at using technology to solve problems motivated from industry and commerce. Students will explore technology to illustrate both problems and their solutions. The emphasis will be to use technology to communicate problems and solutions motivated from industry and commerce. An underlying rational for the module is the extension of the skills of the mathematical professional (MAU402) to utilise technology to communicate problems and solutions to a wider audience.
The module will look at using web-based technology to illustrate solutions to a variety of problems. Students will explore and develop interactive applets to illustrate both problems and their solutions. The emphasis will be to use a web scripting language to solve problems and then to display the results of these on their own personal web sites. An underlying rational for the module is the extension of the skills of the mathematical professional (MAU402) to utilise web and scripting languages to communicate ideas to a wider audience in an interactive manner.
Please note that we no longer offer the option study a semester at Newman University in Wichita, USA – as referenced in our University prospectus.