This degree programme provides a thorough training in statistical methodology and modelling and their application to interdisciplinary problems. In addition, students will learn to use the computer as a tool for analyzing data. To these ends, they acquire essential mathematical skills and a profound knowledge of probability theory and statistics as well as relevant programming skills. Specialized courses in, for example, economics and computer science or lectures in further areas of mathematics beyond statistics supplement this knowledge. Through a combination with courses on more advanced statistical topics, students are able to develop their own individual profile.

The first study year focuses on an application- and data-driven approach to statistics, before, from semester 3, fundamental courses in probability and mathematical statistics lay the foundations for more advanced subjects in the field.

The knowledge and skills acquired during the programme enable graduates to solve statistical problems independently and competently. Moreover, graduates will be able to apply appropriate statistical methods to analyze data in interdisciplinary contexts, to interpret the results correctly and to communicate findings efficiently.

The growing importance of statistics and data science in many economical areas offers graduates of the programme a wide spectrum of occupational prospects and opportunities, with an increasing demand driven by the ongoing digitalization of many businesses and public sectors. Excellent job prospects exist in a variety of areas that are concerned with analyzing data. These include classical statistical positions in the pharmaceutical industry, clinical research, finance and insurance or public administration. Moreover, many companies employ statisticians as data analysts or consultants. Graduates of the programme can furthermore continue their studies and broaden their expertise with a master’s course in statistics, such as the Masterstudiengang Statistik at the Otto-von-Guericke University, or in a related area.

Since all statistical methods are rooted in mathematics in one way or another, prospective students should share a general interest in mathematics and its applications. Computers and programming play an important role in data analysis. Therefore, an interest in computer science will also be helpful, although no programming skills are expected at the start of the programme.

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