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MSci Statistics with Work Placement
About this course
Statistics is the science of making sense of data, developing the mathematical and computational methods needed to collect, analyse and draw reliable conclusions from quantitative information in the presence of uncertainty. It underpins research in medicine, psychology, economics, ecology and the social sciences, as well as the data-driven decision-making that has become central to business, government and technology. As the volume and variety of available data continues to grow, statistical expertise has become one of the most transferable and in-demand quantitative skills available. At the University of Glasgow this five-year degree combines comprehensive statistics training with a work placement, giving you the opportunity to apply your skills in a professional environment during the programme. The degree also includes a year abroad option, broadening your perspective on how statistical science is practised internationally. Glasgow's statistics programmes offer considerable flexibility, with the possibility of combining statistics with subjects including mathematics, computing science, economics, finance, management, psychology and geography, reflecting how widely statistical thinking is deployed across different disciplines. You will develop expertise in statistical theory alongside practical proficiency in the computational and data analysis tools that professionals use. Statistics graduates are exceptionally well positioned in the job market across a range of sectors. Many go on to careers in data science, actuarial work, biostatistics, financial modelling, market research, government statistics services, clinical trials, epidemiology and technology. The combination of mathematical rigour, computational skill and the ability to interpret data clearly makes graduates valuable wherever evidence-based decision-making matters. For those wishing to continue their studies, the degree provides excellent preparation for postgraduate work in statistics, data science, machine learning, operational research or related quantitative disciplines.
Syllabus & Modules
Typical curriculumStudent Satisfaction
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