Master of Science in Applied Statistics

Program overview

This English-language master's trains students in modern, practical statistical methods and prepares them to work as applied statisticians. The curriculum provides a broad grounding in statistics while allowing focused study in one of four specialisations. Because the department’s research concentrates on computational and survey methodology, the programme places particular emphasis on computational (survey) statistics and hands-on data analysis.

Students benefit from on-campus research activity through the Research Institute for Official and Survey Statistics (RIFOSS), and the course structure encourages a multidisciplinary perspective by incorporating subject-matter contexts such as economics and the social sciences. Teaching is extended via collaboration with the University of Bamberg using modern teleteaching facilities, widening the range of lectures available and helping students tailor their study plan to specific career goals.

Four specialisation tracks are offered—Survey Statistics, the European Master in Official Statistics (EMOS), Data Science, and Geostatistics—and there are several international and interdisciplinary options to broaden experience. These include an international double master’s with the University of Pisa, ERASMUS study-abroad opportunities, and combinations with related programmes (e.g., Business Mathematics, Data Science, Economics, Economic Sociology) to customise an individual profile.

Graduates commonly move into national statistical offices, central banks, research institutes, banks, consultancies, market-research firms, international organisations, governmental agencies, or continue with PhD studies (outstanding students may pursue doctoral research at the department). The programme’s location also offers easy access to high-profile internship opportunities near Eurostat (Luxembourg), the German Federal Statistical Office (Destatis) in Wiesbaden, and the Deutsche Bundesbank in Frankfurt.

Key facts and application notes

• Teaching language: English
• Main focus: applied and computational (survey) statistics
• Specialisations: Survey Statistics; European Master in Official Statistics (EMOS); Data Science; Geostatistics
• Research link: Research Institute for Official and Survey Statistics (RIFOSS) on campus
• Collaborations: University of Bamberg (teleteaching); international double degree with the University of Pisa
• Mobility: ERASMUS study-abroad options available
• Flexible double-degree combinations with related programmes (e.g., Business Mathematics, Data Science, Economics, Economic Sociology)
• Typical career destinations: national statistical institutes, central banks, research institutes, banks, consultancies, market-research firms, international organisations, government agencies; PhD/academic paths also possible
• Location advantage: proximity to Eurostat (Luxembourg), Destatis (Wiesbaden), Deutsche Bundesbank (Frankfurt) — strong internship prospects
• Admissions and specific entry requirements (academic prerequisites, language certificates, application deadlines): please consult the university’s official admissions page for up-to-date details.

Overview

This two-year, full-time on-campus Master's programme delivers a comprehensive grounding in modern statistical methods, combining core theory with hands-on computational training and a supervised research component. The curriculum is organised into a mix of required core modules, elective specialisation tracks, interdisciplinary application courses, a research project and a final Master's thesis.

Key modules and study focus

Core compulsory modules include Elements of Statistics and Econometrics, Monte Carlo Simulation Methods, and Statistical Programming with R — ensuring you gain both theoretical foundations and practical coding skills. Elective offerings let you tailor the degree: choose elective core modules linked to a chosen specialisation track, select from general-statistics courses such as Statistical Modelling or Multivariate Statistics, or take application-oriented modules drawn from fields like Data Science, Economics or Sociology. Methodological emphases available across modules include computer-intensive techniques, econometric approaches, Monte Carlo methods and survey sampling.

Teaching format and learning outcomes

The programme emphasises method-oriented lectures supported by tutorials (including programming exercises and e-learning elements) so you develop applied competence as well as conceptual understanding. These taught components prepare you for your own research work: a dedicated research project leads into the Master's thesis, where you apply learned methods to an original problem. Graduates emerge with solid skills in statistical reasoning, practical experience in statistical programming (notably R), and the ability to carry out applied or methodological research in statistics and related fields.

Requirements (curriculum components)

• Programme length and mode: two-year, full-time, on-site study
• Compulsory modules: Elements of Statistics and Econometrics; Monte Carlo Simulation Methods; Statistical Programming with R
• Elective core modules: chosen according to the selected specialisation track
• Elective General Statistics modules: e.g., Statistical Modelling, Multivariate Statistics
• Elective application modules: e.g., courses from Data Science, Economics, Sociology
• Research project (prepares for thesis and first independent research activities)
• Master's thesis (final research-based assessment)

Graduates are prepared for roles in national statistical institutes (NSIs), central banks, quantitatively oriented research institutes and governmental agencies. The programme’s applied and computational training also suits careers in banks, investment firms, consultancies, market research companies and international organisations.

Excellent graduates may pursue PhD studies and academic careers; the research orientation and the partnership with RIFOSS support early research activity and doctoral preparation.