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Lund University

Master Programme in Mathematical Statistics

<p>Do you want to understand how random sequences of events can be described mathematically? Would you like to build models of reality based on collected data? Expertise in mathematical statistics is a highly sought-after qualification in both academia and industry.</p><p>This Master’s programme gives you the opport…

  • Higher education
  • Information unavailable
  • 31 August 2026
  • Information unavailable
  • Information unavailable
  • 100 %

Overview

<p>Do you want to understand how random sequences of events can be described mathematically? Would you like to build models of reality based on collected data? Expertise in mathematical statistics is a highly sought-after qualification in both academia and industry.</p><p>This Master’s programme gives you the opportunity to take a deep dive into the fascinating world of probability and chance. The entire programme is taught in English. </p><p>As a student, you will acquire solid skills in probability theory, statistical theory and methodology. You will learn a number of different methods enabling the application of mathematical statistics in fields such as biology, medicine, the environment, climate, risk management and economics. </p><p>For example, you might analyse genetic links to congenital diseases, or how a slowly changing climate can lead to extreme weather events. Statistical risk management can also be used in models concerning structural safety, and wear and tear in construction, among other areas. You will also have the opportunity to learn to work with financial applications in the form of models for pricing, optimisation of electricity trading, risk management and various forms of financial forecasting. </p><p>The Master’s programme is strongly linked to research. All teaching staff on the programme are active researchers. The proportion of teacher-directed learning is high. You practise both oral and written communication and gain good experience of collaboration in groups. The programme’s course structure gives you an excellent opportunity to shape your own profile.</p><p> </p><p> </p><p> </p>

Admission scores

Uppgift saknasVerified data is not connected to this education offering.

Entry requirements

Bachelor’s degree of at least 180 credits or the equivalent, including at least 90 credits in mathematics, mathematical statistics, numerical analysis, scientific calculations and computer science, of which at least 45 credits must be in mathematics that include courses in multivariate analysis and linear algebra, at least 30 credits in mathematical statistics and at least 15 credits in numerical analysis, scientific calculations and/or computer science. Proficiency in English equivalent to English 6/B from Swedish upper-secondary school.

The text is reproduced from the Susa source. Antagningsdata does not map GY11 and GY25 or assess personal eligibility.

Source, measure and data quality
Source
Skolverket Susa-navet
Period
2026-08-31
Measure
Entry-requirement text reproduced from the published Susa data; no personal eligibility assessment is made.
Population
Education offering e.uoh.lu.namas.18150.20262
Last checked
2026-09-23T10:38:33.477975+00:00
Limitation
Antagningsdata does not map GY11 and GY25. General and specific conditions are not separated without structured source data.

Programme content

Uppgift saknasVerified data is not connected to this education offering.

Study structure

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Application and important dates

  1. Programme or course starts
  2. Programme or course ends

Salary and salary distribution

Uppgift saknasVerified data is not connected to this education offering.

Common occupations after graduation

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Students

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Geographical background

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Previous upper-secondary schools and programmes

Uppgift saknasVerified data is not connected to this education offering.

Completion and outcomes

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About the provider

Lund University

Provider for the published education offering.

Sources and data quality

Education facts for the selected offering come from Skolverket Susa-navet.

Retrieved . Published . Times are shown in Swedish local time.

Source identity and publication version
Publication version
8e217193-f5fa-4778-b085-a4521fd03e8d
Education identity in the source
i.uoh.lu.namas.18150.20262
Offering identity in the source
e.uoh.lu.namas.18150.20262
Education-form source code
HS
Education code in the source
NAMAS
Change time according to the source
2026-02-10T09:42:40

The provider, education and education offering are separate identities. Application information should be checked on the official website. Supplementary statistics have not been obtained from this source.