Applied Statistics, M.Sc.
Registration Periods for Master Courses!
Open enrollment from 11.02.22 to 29.01.23.
EXCEPTION: Research Case Studies and Survey Statistics Research Project
Strong application orientation
The goal of the master's degree is to integrate students into application-oriented research.
In the course of the studies a research project is completed, in which the integration into an existing research project should preferably be advanced (see e.g. current research projects).
The integration into the current research project particularly promotes key competencies such as the ability to work in a team, initiative and communication skills.
Furthermore, it is possible to replace the research project with an external research internship. In this case, the nearby institutions Eurostat, the German Federal Statistical Office or the European Central Bank are potential, attractive contact points, in which the learned statistical-methodical skills are to be used in current research questions with a strong application reference. This enables a direct transition of the master's degree into practice and the diffusion of practical and theoretical knowledge in both directions.
Close ties to the university chair
A special supervision concept provides for students to be accompanied by lecturers during their course of study. This supports an optimal design of the studies.
The research module in particular ensures close integration into the team of the professorship. In addition to the practical application of what has been learned, this is also intended to promote research skills. Furthermore, teamwork and communication skills are strengthened.
Contact
Prof. Dr. Ralf Münnich (Programme Coordinator)
Dr. Florian Ertz (Academic student advisor)
Course of study (M.Sc. Survey Statistics)
The current module handbook can be found here.
The Master's program is based on the following statistics modules and module groups, regardless of the chosen orientation:
1. Basics
- Survey Sampling
- Elements of statistics and econometrics
2. Statistical Programming and Computer-intensive Methods
- Statistical Programming and Computer-intensive Methods
- Monte-Carlo simulation methods
2. Survey Statistics
- Weighting and calibration
- Variance Estimation
- Introduction to Bayes statistics
- Statistical analysis of incomplete data
- Panel Surveys
- Indicators of Economics and Social Statistics
- Statistical Disclosure Control
- Small Area Estimation
- Survey Econometrics
- Modern Methods in Survey Statistics
- Methods of Survey Statistics
- Survey Methodology
- Optimization in Survey Statistics
- Use of Non-sampling Data
- EMOS Core
3. Statistics
- Multivariate Statistics
- Statistical Modeling
- Experimental Design
- Optimization Methods in Statistics
- Statistical Literacy
4. Application
- Application
- Official Statistics
- EMOS
5. Research Project
6. Master's thesis
In these modules, advanced methods of statistics in general and inferential statistics in particular are taught, as well as further methodological and content-related emphases. These include, for example, methods of econometrics or Monte-Carlo techniques and computer-intensive procedures on the one hand and special courses in survey statistics on the other. The method-oriented courses promote the understanding of the application-oriented modules. In addition, they lay the foundation for the students' own initial research activities, which are to be learned and developed in the research module.
Detailed information on the contents, examination modalities and significance of the individual module components, as well as numerous other useful information can be found in the preliminary module handbook. The module handbook is valid under reserve due to pending minor linguistic changes.
Course of study Survey Statistics M.Sc
Master's theses
Master's theses at the Economic and Social Statistics Department usually deal with topics of survey statistics or related topics. Therefore, a solid basic knowledge of survey statistics is usually required.
If you plan to write your master's thesis at the Economic and Social Statistics Department, please contact Dr. habil. Jan Pablo Burgard (burgardjuni-trierde).