BSc Statistics
About this course
Statistics is the science of learning from data, providing the tools and frameworks needed to collect, analyse and interpret information in the face of uncertainty. It sits at the foundation of modern science, medicine, economics and public policy, and its importance has grown enormously as the volume of data generated by digital systems, scientific instruments and commercial activity has increased. Whether the question is how to design a clinical trial, model financial risk, understand election results or train a machine learning algorithm, statistical thinking is essential. At the University of Nottingham, this three-year programme includes a foundation year for those who need to consolidate their mathematical background before progressing to degree-level work, and a sandwich year that allows you to spend time in a professional setting before your final year. A work placement is also available, giving you direct experience of applying statistical methods in industry or a research environment. You will study probability theory, statistical inference, regression and linear models, time series analysis and Bayesian methods, as well as computational statistics and the use of software tools for data analysis. The degree develops both mathematical rigour and practical data skills, so you can move between formal theoretical work and applied problem-solving with confidence. The sandwich year is a particularly valuable element of the programme. Statistics graduates are in demand across almost every sector, and spending a year working with real data in a real organisation gives you a clear advantage when you enter the graduate labour market, as well as helping to confirm where you want your career to go. Statisticians work in a remarkably wide range of fields. Government statistical services, financial institutions, pharmaceutical companies, consultancies, technology firms and academic research groups all recruit graduates from this discipline. Roles include data analyst, statistician, actuary (with further professional study), risk analyst and quantitative researcher. The programme also provides an excellent foundation for postgraduate study in statistics, data science, operational research or related disciplines.
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