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Develop a comprehensive toolkit of statistical methods and approaches to tackle challenges across various sectors. You'll acquire the expertise required for a career as a professional statistician.
This program covers the theoretical foundations of diverse statistical methods and their practical application in real-world situations commonly encountered by statisticians.
You'll gain in-depth proficiency in key statistical concepts and methodologies, such as linear and generalized linear modeling, Bayesian statistics, time series analysis, and machine learning. You'll master techniques for interpreting data effectively while enhancing your programming abilities through R statistical software.
The curriculum also features components on experimental design, data collection methods, and statistical applications in clinical trials.
Approximately one-third of the program focuses on your dissertation project. This could involve analyzing datasets or exploring theoretical/methodological questions, equipping you with valuable CV skills including project planning, research methodology, data gathering, problem definition, analytical techniques, and results presentation.
Dissertation subjects frequently originate from external partners like pharmaceutical firms or sports analytics organizations. Distance learners often undertake projects aligned with their employer's needs.
Career prospects
Upon graduation, you'll possess specialized modeling and analytical capabilities highly sought after by employers working with complex datasets in diverse fields - from business, manufacturing, and marketing to public policy, scientific research, and healthcare.
Our Mathematics and Statistics graduates have secured positions with leading organizations including Amazon, Barclays, Dell, Goldman Sachs, IBM, PwC, Sky, the NHS, and government agencies.
This qualification meets the requirements for the Royal Statistical Society's Graduate Statistician accreditation - a pathway to full RSS membership and Chartered Statistician designation.