Master Programme in Mathematical Statistics

Programme overview

  • Master's Programme, 2 Years, Full time
  • Code: LU-18050
  • 120 credits
  • Lund Campus
  • Study period: 01 Sep 2014 – 05 Jun 2016

The Master?s programme in Mathematical Statistics provides a broad spectrum of tools and methods for handling random phenomena occurring in scientific as well as industrial contexts. Within the programme you can specialise in many different areas for different purposes. In this programme you take at least 45 ECTS credits in mathematical statistics at Master s level, and write a Master?s thesis of 30 ECTS credits. You can choose to take the remaining (at most) 45 ECTS course credits in mathematics or numerical analysis. You can also choose to take courses in other subjects such as computer science, or, if you are aiming for a career in a specific applied field, courses in that field. Examples include courses in economics, molecular biology and bioinformatics. If you intend to proceed to a PhD you should take courses with a high degree of theory content, while if you are aiming for a career outside academia you should take courses that cover a wide range of statistical models and methods.

Career prospects
With a Master of Science in Mathematical Statistics you have great opportunities to form an exciting career in, for example, the pharmaceutical industry, biotechnology companies or the banking and finance sector. Statistical methods are also of great importance for logistics, quality assurance and development in industry, and organisations within the public sector.

More information can be found at http://www.maths.lu.se/english/education/mathematical-statistics-masters-programme/

Late applications are being accepted

  • Shilpy Madan, alumna from India

    “I chose Lund University because it is one of the best universities in the field of Mathematics and Statistics, and rightly so. I was introduced to a variety of highly intriguing subjects, subjects that pertained to statistics in the field of finance, medicine, extreme events and more. We were given real time projects, whose difficulty level was fairly high and to be submitted on deadlines, but this helped us get ready for the projects and problems that await us in the real world. We worked on the latest and most widely used softwares in the industry these days. There was always a perfect blend of theoretical and practical knowledge. All professors had excellent knowledge and expertise in their respective field of study and were easily approachable."

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