Gain extensive knowledge of probability and statistics. Combine this with pure mathematics or applied mathematics. This degree will equip you with problem-solving and decision-making tools. You'll experience using statistical software and practise conducting and communicating statistical investigations. You'll develop your understanding of time series analysis, multivariate data analysis, regression analysis, and hypothesis testing. You'll also explore classical and Bayesian statistics.
Take your understanding of concepts, theories and applications in pure and applied mathematics to graduate level. You can also include optional statistics, theoretical physics or mathematics education. You'll cover a wide range of topics and develop an understanding of mathematical problems and approaches. Practise with essential methods and tools, and increase your familiarity with mathematical software. Gain an appreciation of the role and construction of rigorous proof. And build your experience of communicating mathematical arguments and conclusions.
Understand how people learn mathematics and gain insight into different teaching approaches. We designed this unique degree with those interested in teaching mathematics ? or in education more generally ? in mind. It will develop your knowledge and understanding of mathematics and statistics teaching. And broaden your ideas about what it means to learn and teach these subjects. You'll also gain a good grounding in mathematics (pure and applied) and statistics. You can focus your studies on either discipline alongside mathematics education.
Develop your knowledge and understanding of theoretical physics and the underpinning mathematics. This degree will teach you how to use essential techniques and relevant software. Explore fundamental physics concepts, including Newtonian mechanics, special relativity, electromagnetism and quantum mechanics. Practise using applied mathematics tools, including mathematical methods, modelling and numerical methods. You'll also learn skills in communicating clear and concise arguments and conclusions.
If you enjoy solving problems and you're interested in the practical application of economics and mathematics, this degree could be what you're looking for. It'll give you a thorough grounding in mathematical, statistical and computational skills, and a sound knowledge of both micro and macro-economic theory ? together with a good understanding of economic issues. By the end of your studies, you'll have a level of numeracy and understanding of the commercial and economic environment that's in short supply to employers.
This diploma will give you a thorough grounding in pure and applied mathematical concepts, theories and their uses, with the option to combine them with statistics to suit your needs and interests. You'll get practice with essential methods and tools; gain an appreciation of abstract mathematics and mathematical modelling; increase your familiarity with mathematical software; and build experience of communicating mathematical arguments and conclusions.
This certificate provides the basic skills you need for further study in mathematics and statistics, and is ideal if you need some mathematics to underpin your studies in other areas. You'll be introduced to pure mathematics, applied mathematics and statistics; using mathematical software; working with abstract ideas; and modelling real-world problems using mathematics.
You'll study in greater depth, to expand your development as an engineer, the underpinning science and mathematics; engineering analysis; design; environmental and economic context; and engineering practice introduced in earlier engineering study. Further development of reflective engineering practice is integral throughout. You'll discuss aspects of your study with other students and your tutor, conduct remote experiments using our award-winning OpenEngineering remote laboratories, and use industry-recognised software.
This introductory module examines the range of human activity that is 'engineering', setting current practice in a historical context and looking forward to new developments that will help shape the future. Key scientific principles, mathematical techniques and design methodologies are introduced and explained, to equip you with a basic toolkit on which to build further study. Mathematics is presented in an engineering context to emphasise relevance and build your confidence in framing problems, addressing design challenges and formulating solutions. Reflective practice is encouraged throughout and you will have the opportunity to share and discuss aspects of your work with other students.
This key introductory OU level 1 module provides a gentle start to the study of mathematics. It will help you to integrate mathematical ideas into your everyday thinking and build your confidence in using and learning mathematics. You'll cover statistical, graphical, algebraic, trigonometric and numerical concepts and techniques, and be introduced to mathematical modelling. Formal calculus is not included and you are not expected to have any previous knowledge of algebra. The skills introduced are required for successful study in many subject areas, such as in computing, economics, science, technology, social science, humanities, business and education. And they're needed if you plan to study further mathematics modules, such as (MST124).
This module teaches advanced mathematical methods with the aid of Maple, an algebraic computing language with graphics and numerical capabilities, which you'll be taught how to use. Although the emphasis is on mathematical methods, you'll use Maple partly to extend the use of these methods, partly to help you to visualise the mathematics and partly to enable you to combine conventional analytic techniques with numerical methods. You'll explore various forms of approximations, perturbation expansions, and accelerated convergence methods including Pad? approximants, asymptotic expansions of integrals and some eigenvalue problems.
Analytic number theory is a vibrant branch of mathematics concerned with the application of techniques from analysis to solve problems in number theory. In this intermediate-level module, which is a sequel to (M823)you'll learn about a rich collection of analytic tools that can be used to prove important results such as the prime number theorem. You'll also be introduced to the Riemann hypothesis, one of the most famous unsolved problems in mathematics. Before embarking on M829, you should have completed a module in complex analysis, covering topics such as the calculus of residues and contour integration.