BSc Mathematics and Statistics

This course provides a comprehensive education in mathematics and statistics, equipping students with the skills and knowledge to analyze and interpret complex data sets. The program covers a wide range of topics including calculus, linear algebra, probability, statistical inference, and computational methods. Students will also have the opportunity to specialize in areas such as financial mathematics, actuarial science, or machine learning. The course is designed to provide students with a solid foundation in mathematical and statistical principles, as well as the practical skills necessary for a successful career in data analysis.

Additional Information

This course is delivered through a combination of lectures, seminars, and practical sessions. Students will also have access to state-of-the-art computing facilities and software packages. The course is designed to be challenging but rewarding, with a focus on developing problem-solving skills and critical thinking. Graduates of this program will be well-prepared for careers in academia, industry, or government.

Experience the best of UK academia at Durham University - Study Group

Durham University is one of the top universities in the UK, known for its academic excellence and research opportunities. The Study Group campus provides a supportive learning environment with access to world-class facilities and faculty. Students can benefit from a range of extracurricular activities and networking opportunities, providing a well-rounded education.

Methods of teaching and learning used in the course include a mix of lectures, tutorials, problem classes, computer practicals, homework problems (including electronic assessment), written and oral presentations, and individual projects. A variety of modes of assessment will be used and are likely to include written examinations, computer-based examinations, project reports, presentations of project work. Much of the teaching in mathematics and statistics consists of 50-minute lectures (12 per week on average) in which lecturers will explain concepts, derive results, state and prove theorems, and work through analytical and computational examples, developing motivation, understanding, and technique. The best way to consolidate and fully internalize this knowledge is to use it. In the first two years, lectures are supplemented by tutorials, informal small classes (about 12 in the first year and 16 in the second year) in which students work through problems and ask questions. You will have at least three per week during each of the first two years. Many of the statistics modules across all three years also include computer practicals, in which students learn how to implement computational methods and how to analyze real data. Homework problems and exercises are set in lectures, and your marked solutions may form the topic of discussion in a tutorial or problem class. You will be encouraged to work with other students, and to make use of the University's library and computing resources.

A level offer €“ A*A*A-A*AA.