BSc Mathematics and Statistics
About this course
Mathematics and statistics is a combination that takes two closely related but distinct mathematical disciplines and allows you to develop genuine depth in both. Pure and applied mathematics provide the theoretical foundations and analytical tools that underpin quantitative reasoning across science, engineering, finance and computing. Statistics is the discipline concerned with collecting, analysing, interpreting and communicating data, making it one of the most practically valuable branches of mathematics in an era when data-driven decision-making has become central to organisations in every sector. At Queen Mary University of London this four-year full-time programme is shaped by the recognition, expressed in the course's own description, that we generate an ever-increasing volume of data every day and that the ability to analyse, interpret and communicate data through statistical analysis is an increasingly important professional skill. You will develop rigorous mathematical knowledge across analysis, algebra and applied mathematics alongside deep statistical training covering probability theory, statistical modelling, inference, data analysis and modern computational methods. Queen Mary has strong mathematics research activity and is located in London, one of the world's major financial and technology centres, both of which shape the learning environment and the professional opportunities available to graduates. You will develop mathematical precision, the ability to construct and evaluate arguments from first principles, and the statistical fluency to work confidently with complex datasets and models. These are among the most transferable skills that any degree provides. Graduates pursue careers in data science, actuarial science, financial services, insurance, pharmaceutical statistics, operational research, government analysis, technology and education. Many pursue professional qualifications in actuarial science or statistics, and postgraduate study in statistics, data science, machine learning or applied mathematics is a well-established route for those who want to develop specialist expertise.
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