Qualification objectives of the Master's programme in Survey Statistics and Data Analysis 

Competency-oriented teaching is becoming more and more central in the course of the Bologna Process. This also brought with it the formulation of qualification goals. Qualification goals are intended to make a statement about which competences one has acquired with the completion of a degree programme. The competences mentioned are based on the Qualifications Framework for German Higher Education Degrees (HQR). The Master's programme in Survey Statistics leads to a professional and research-qualifying degree at a scientific university.

Completion of the Master's programme also lays the foundation for subsequent academic qualifications, for example a doctorate.

Scientific qualification

From John W. Tukey, one of the most famous statisticians of the 20th century, the following quote has come down to us: "The best thing about being a statistician is that you get to play in everyone's backyard." The sound training in applied statistics and quantitative methods enables graduates of the Master's programme Survey Statistics to gain a foothold not only in statistics, but also in substance sciences in which statistical methods are used.

• After completing the specialist modules (e.g. Statistical Machine Learning or Introduction to Bayesian Statistics), graduates of the Master's programme in Survey Statistics and Data Analysis are able to think analytically in depth and confidently formulate implicit and explicit assumptions that underlie the models used in the description of empirical phenomena.
• Through independent research projects in the Master's programme and their presentation in term papers and lecture posters in the examination requirements of various compulsory and compulsory elective modules such as "Statistical Analysis of Incomplete Data" or "Small Area Estimation Methods", graduates are prepared for writing scientific articles and creating conference posters and are able to engage in critical discourse, incorporating their own findings and taking into account generally accepted principles of good scientific practice.
• Graduates are familiar with the current state of research in the field of statistics and are able to apply and further develop this knowledge in the context of independent research. In addition to the regular methodology modules, these skills are based on workshops that take place regularly in Bamberg and are eligible for credit towards the Master's degree. Furthermore, the curriculum is supplemented by application-oriented modules, in which current topics in statistical research also play an important role.
• With their final thesis, graduates have demonstrated that they are capable of planning independent research and implementing it in accordance with scientific standards, for example on a topic of their own choosing or within the framework of an external cooperation in the field of science or industry. In the accompanying colloquium, they have demonstrated that they can present their research in a lecture and respond to critical questions and suggestions.

Qualification for skilled employment

• For a career in statistics or data science, graduates have acquired relevant skills, for example in the areas of statistical modelling, sampling theory or the analysis of high-dimensional data, graduates have acquired the skills to flexibly prepare a wide variety of data structures for different analyses, to apply statistical models professionally, taking into account the relevant assumptions, and, if necessary, to expand them by developing and implementing their own functions or models with the help of statistical programming languages.
• Through compulsory and elective modules, graduates acquire in-depth knowledge of the programming languages R and Python and are able to perform statistical programming and visualise and interpret their results.
• Graduates have honed their profile in modules from the 'Application' module group (e.g. by taking modules from other degree programmes) and acquired additional programming skills that they can apply in new contexts.
• Internationality is also important for this Anglo-Saxon-dominated academic discipline. Graduates acquire specialist language skills from the modules taught in English, which they have consolidated through (poster) presentations and can apply in professional contexts.
   

Personal development

• The course of study itself contributes to a process of personal maturation. Due to variable module group sizes and flexible specialisations in the area of application modules, graduates have independently refined the focus of their studies and optimised it with regard to their future career aspirations.
• Through their practical experience gained during internships and research projects – and also through feedback from colleagues and supervisors – graduates have strengthened their confidence in their own knowledge and abilities. They can accurately assess their own abilities and have developed a professional self-image based on this.
• They can take on responsibility within the framework of the professional values of their job or profession and independently acquire the latest research findings in the field of statistics through their own further training.
• In group work and oral examinations, graduates have further developed their teamwork and communication skills in a professional context. They are able to work together in a team-oriented manner to develop solutions and to communicate and explain their knowledge verbally, even in critical discussions with (specialist) audiences.
• During their stay abroad, graduates also acquired intercultural skills, developed their personalities and self-organisation skills, and gained international experience, for example in teamwork, as part of an optional study abroad programme, such as an Erasmus stay at the University of Florence or individual study abroad programmes. In doing so, they have demonstrated their ability to communicate and act professionally in intercultural teams.
• Thanks to their in-depth knowledge of statistics and data analysis, graduates are able to contribute to improving the data basis used, for example, as a foundation for political decision-making processes within the scope of their professional activities.
• Furthermore, this in-depth knowledge helps graduates of the Master's programme in Survey Statistics and Data Analysis to explain methodological issues precisely to audiences outside their field and to define implicit and explicit assumptions correctly.
• In general, graduates are able to prepare data-based information as a basis for decision-making in such a way that transparency in socially relevant decisions is improved. This enables them to play a decisive role in shaping social processes in a critical and reflective manner, with a sense of responsibility and democratic public spirit.