Overview
The Master of Statistics (MStat) is an advanced quantitative degree in probability, statistical theory, computation and applications. It is suited to graduates with strong mathematics who want deeper preparation for data-intensive industry, research or public decision-making.
What students study
Common areas include measure-based probability, inference, linear models, multivariate analysis, stochastic processes, sampling, Bayesian methods, optimisation, computing and specialised applications. The programme may include rigorous proofs, programming, projects and a dissertation.
Duration and study options
MStat is commonly a two-year full-time programme. Compare prerequisite mathematics, theoretical depth, software and computing access, applied projects, research groups, internships and how the curriculum differs from MSc Statistics or data-science degrees.
Eligibility and admission
Applicants generally need a recognised bachelor’s degree with substantial mathematics or statistics and the credits and marks specified by the institution. Selection may use an institution entrance test, qualifying marks, interviews, CUET-PG where adopted or other published criteria.
Career and further study
Graduates enter statistics, data science, risk, finance, technology, government, research, biostatistics and quantitative consulting. Options include PhD, research fellowships, econometrics, actuarial science, operations research, machine learning and specialised applications.
Student checklist
Before applying, compare the syllabus, recognition or regulatory approval where applicable, delivery mode, fees, practical training, entrance requirements and placement support. Always confirm the current rules with the university or admission authority.
Important: Course structures, duration, eligibility and professional recognition can vary by university, specialisation and academic year. Use this overview for planning and verify the latest prospectus before applying.